Data Scientist remote jobs

We are looking for a Data Engineer in Austin, TX (fully remote - MUST work CST hours). Job Title: Data Engineer Contract: 12 Months Hourly Rate: $75- $82 per hour (only on W2) Additional Notes: Fully remote - MUST work CST hours SQL, Python, DBT, Utilize geospatial data tools (PostGIS, ArcGIS/ArcPy, QGIS, GeoPandas, etc.) to optimize and normalize spatial data storage, run spatial queries and processes to power analysis and data products Design, create, refine, and maintain data processes and pipelines used for modeling, analysis, and reporting using SQL (ideally Snowflake and PostgreSQL), Python and pipeline and transformation tools like Airflow and dbt • Conduct detailed data research on internal and external geospatial data (POI, geocoding, map layers, geometrics shapes), identify changes over time and maintain geospatial data (shape files, polygons and metadata) • Operationalize data products with detailed documentation, automated data quality checks and change alerts • Support data access through various sharing platforms, including dashboard tools • Troubleshoot failures in data processes, pipelines, and products • Communicate and educate consumers on data access and usage, managing transparency in metric and logic definitions • Collaborate with other data scientists, analysts, and engineers to build full-service data solutions • Work with cross-functional business partners and vendors to acquire and transform raw data sources • Provide frequent updates to the team on progress and status of planned work About us: Harvey Nash is a national, full-service talent management firm specializing in technology positions. Our company was founded with a mission to serve as the talent partner of choice for the information technology industry. Our company vision has led us to incredible growth and success in a relatively short period of time and continues to guide us today. We are committed to operating with the highest possible standards of honesty, integrity, and a passionate commitment to our clients, consultants, and employees. We are part of Nash Squared Group, a global professional services organization with over forty offices worldwide. For more information, please visit us at ****************************** Harvey Nash will provide benefits please review: 2025 Benefits -- Corporate Regards, Dinesh Soma Recruiting Lead

This is a fully remote 12+ month contract position. No C2C or 3rd party candidates will be considered. Data Engineer (AI & Automation) We are seeking a Data Engineer with hands-on experience using AI-driven tools to support automation, system integrations, and continuous process improvement across internal business systems. This role will focus on building and maintaining scalable data pipelines, enabling intelligent workflows, and improving data accessibility and reliability. Key Responsibilities Design, build, and maintain automated data pipelines and integrations across internal systems Leverage AI-enabled tools to streamline workflows and drive process improvements Develop and orchestrate workflows using Apache Airflow and n8n AI Model, transform, and optimize data in Snowflake and Azure SQL Data Warehouse Collaborate with business and technical teams to identify automation opportunities Ensure data quality, reliability, and performance across platforms Required Qualifications Experience as a Data Engineer or similar role Hands-on experience with Apache Airflow and modern workflow orchestration tools Strong experience with Snowflake and Azure SQL Data Warehouse Familiarity with AI-driven automation and integration tools (e.g., n8n AI) Strong SQL skills and experience building scalable data pipelines Preferred Qualifications Experience integrating multiple internal business systems Background in process improvement or operational automation Experience working in cloud-based data environments (Azure preferred)

At ServiceLink, we believe in pushing the limits of what's possible through innovation. We're looking for a high-achieving AI enthusiast to lead ground-breaking initiatives that redefine our industry. As our Principal Data Scientist, you'll harness cutting-edge technologies-from advanced machine learning and deep learning to generative AI, Large Language Models, and Agentic AI-to create production-ready systems that solve real-world challenges. This is your opportunity to shape strategy, mentor top talent, and turn ambitious ideas into transformative solutions in an environment that champions bold thinking and continuous innovation. Applicants must be currently authorized to work in the United States on a full-time basis and must not require sponsorship for employment visa status now or in the future. A DAY IN THE LIFE In this role, you will… Transform complex business challenges into innovative AI solutions that leverage deep learning, LLMs, and autonomous Agentic AI frameworks. Lead projects end-to-end-from ideation and data gathering to model design, fine-tuning, deployment, and continuous improvement using full MLOps practices. Collaborate closely with business stakeholders, Data Engineering, Product, and Infrastructure teams to ensure our AI solutions are powerful, secure, and scalable. Drive both research and production by designing experiments, publishing state-of-the-art work in high-impact journals, and protecting strategic intellectual property. Mentor and inspire our next generation of data scientists, sharing insights on emerging trends and best practices in AI. WHO YOU ARE You possess … A visionary leader with an advanced degree (Master's or Ph.D.) in Computer Science, Engineering, or a related field, backed by 10+ years of progressive experience in AI and data science. A technical powerhouse with a solid track record in statistical analysis, machine learning, deep learning, and building production-grade models using transformer architectures and Agentic AI systems. Proficient in Python-and comfortable with other modern programming environments-armed with real-world experience in cloud platforms (preferably Microsoft Azure) and end-to-end AI development (CRISP-DM and ML-Ops). An exceptional communicator who can distill complex technical ideas into strategic insights for diverse audiences, from the boardroom to the lab. A proactive problem solver and collaborative team player who thrives in a fast-paced, interdisciplinary setting, ready to balance innovative risk with practical execution. Responsibilities Strategize with leadership and stakeholders to align AI innovations with business objectives-identifying risks, seizing opportunities, and driving measurable outcomes. Architect and lead the development of next-generation AI solutions, with a special focus on Agentic AI, deep learning models, and transformer-based LLMs. Build automated MLOps pipelines to ensure continuous integration, deployment, and monitoring of models across diverse data environments. Act as both a thought leader and an active contributor-publishing in high-impact journals, representing ServiceLink at industry events, and safeguarding our IP. Collaborate cross-functionally to ensure our AI systems are secure, scalable, and cost-effective, continuously refining them based on rigorous performance metrics Mentor and empower your peers, fostering a culture of innovation, resilience, and learning. All other duties as assigned. Qualifications Advanced degree (Master's or Ph.D.) in Computer Science, Engineering, or a related quantitative discipline, backed by 10+ years of relevant industry experience. Demonstrated expertise in Python and practical experience deploying advanced ML/AI solutions-including deep learning, LLMs, and Agentic AI-in production environments. Proficiency with modern cloud platforms (preferably Microsoft Azure) and a proven record of operationalizing AI via MLOps best practices. Strong ability to balance innovation with practicality, evaluating technical capabilities versus business and cost considerations. Excellent communicator with a knack for translating intricate technical strategies into clear, actionable plans. A collaborative mindset with a history of mentoring teams and building high-impact technology solutions. We can recommend jobs specifically for you! Click here to get started.

You will be a strategic partner to product, engineering, and trust and safety teams, responsible for defining evaluation frameworks, leading experiments (A/B, quasi-experiments, etc.), and turning offline and live model performance into product improvements. This role requires a strong track record in startup-style experimentation (moving quickly with scrappy but rigorous methods) and product experimentation at scale. The ideal candidate will also bring proven experience in leading and managing teams to deliver high-impact data science work. 100% remote Salary Range $120,000 - $260,000 Essential Job Functions ● Lead end-to-end experimentation: hypothesis generation, metric design, experiment design (A/B, multivariate, sequential, etc.), analysis, and interpretation. ● Build and maintain evaluation frameworks for LLMs: correctness, consistency, safety, hallucination detection, bias/fairness, etc. ● Develop predictive models, classification/ranking systems, and heuristics to improve product features related to AI/language generation. ● Collaborate with prompt engineers & model builders to test prompt strategies, fine-tuning, or model selection; work on failure modes/error analysis. ● Automate experiment pipelines: dashboards, monitoring, alerting, instrumentation. Ensure data quality & measurement integrity. ● Use causal inference / observational studies when randomized experiments are not feasible. ● Present findings and recommendations to both technical and non-technical leadership; influence roadmap decisions. ● Drive experimentation in startup-like environments: rapid iteration, learning from limited data, and balancing speed with rigor. ● Shape large-scale product experimentation: define frameworks for experimentation at scale and integrate results into product strategy. ● Lead and mentor teams of data scientists, analysts, and engineers; set best practices for experiment design and AI product evaluation. Requirements ~8-12+ years of experience in data science / ML roles, ideally with experiment design/product analytics. Proven track record in both startup-style and large-scale product experimentation. Experience leading teams, setting strategy, and driving execution in cross-functional environments. Strong background with statistical methods, causal inference, and rigorous measurement. Experience using LLMs / NLP / AI / prompt engineering or a closely related field. Excellent coding skills in Python (or similar), strong SQL, experience building and deploying models or analytic pipelines. Ability to work in cross-functional teams, translate technical results into business or product changes. Strong communication skills; ability to explain complex analyses to non-technical stakeholders. Preferred Qualifications Experience fine-tuning or working with multiple LLM providers / APIs. Experience with experiment platforms or building internal tooling for experimentation & model evaluation. Experience in voice / ASR or other multi-modal data. Benefits Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k) Life Insurance (Basic, Voluntary & AD&D) Flexible Paid Time Off Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Work From Home Stock Option Plan

May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think. Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We're building the world's best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we've given more than 300,000 autonomy-enabled rides to real people around the globe. And we're just getting started. We're hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us. Lead Data Scientist May Mobility is experiencing a period of significant growth as we expand our autonomous shuttle and mobility services nationwide. We are seeking talented data scientists and machine learning engineers to develop automated methods for tagging data collected by our autonomous vehicles. This will enable us to generate valuable insights from our data, making it easily searchable for triaging issues, creating test sets, and building datasets for autonomy improvements. Join us and make a crucial impact on our development and business decisions! Responsibilities Work independently with cross functional teams to develop software and system requirements. Design, implement, and deploy state-of-the-art machine learning models. Monitor the performance of the auto-tagging system and drive continuous improvement. Lead team code quality activities including design and code reviews. Communicate complex analytical findings and model performance metrics to both technical and non-technical stakeholders through clear visualizations and presentations. Provide technical guidance to team members. Skills Expertise in deep learning, with hands-on experience in the design, training, and evaluation of a wide range of algorithms. Ability to build and productionize machine learning models and large-scale systems. Awareness of the latest advancements in the field, with the ability to translate innovative concepts into practical solutions for May. Excellent problem-solving skills with a meticulous approach to model architecture and optimization. Ability to provide individual and team mentorship, including technical leadership for complex projects. Strong understanding of data labeling best practices, label consistency, and performance metrics specifically relevant to large-scale auto-tagging accuracy and dataset curation. Qualifications and Experience Required B.S, M.S. or Ph.D. Degree in Engineering, Data Science, Computer Science, Math, or a related quantitative field. 10+ years of hands-on experience as a Data Scientist or ML Engineer with a strong focus on algorithmic design and deep learning. Expert-level programming skills in Python with extensive use of modern deep learning frameworks like TensorFlow or PyTorch. Demonstrated experience in building and deploying production-level machine learning systems from conception to delivery. Experience working with multimodal data like visual data (images/video), structured perception and behavior outputs (e.g., agent tracks, vehicle state estimation, motion planner outputs). Demonstrated expertise in databases for data extraction, transformation, and analysis. Prior experience in mentoring and supporting junior engineers. Desirable Background in robotics or autonomous systems. Experience with multi-modal deep learning models, transformers, visual learning models (vLMs) etc. Experience with classifying driving maneuvers and traffic interactions using machine learning methods. Solid understanding of ML deployment lifecycle, MLOps practices, and cloud computing platforms (e.g., AWS, GCP). Expertise in PySpark/Apache Spark for handling large-scale data processing. Physical Requirements Standard office working conditions which includes but is not limited to: Prolonged sitting Prolonged standing Prolonged computer use Lift up to 50 pounds Remote role based out of Ann Arbor, MI. Remote employees work primarily from home or an alternative work space. Travel requirements - 0% The salary range provided is based on a position located in the state of Michigan. Our salary ranges can vary across different locations in the United States. Benefits and Perks Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate. Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available. Rich retirement benefits, including an immediately vested employer safe harbor match. Generous paid parental leave as well as a phased return to work. Flexible vacation policy in addition to paid company holidays. Total Wellness Program providing numerous resources for overall wellbeing Don't meet every single requirement? Studies have shown that women and/or people of color are less likely to apply to a job unless they meet every qualification. At May Mobility, we're committed to building a diverse, inclusive, and authentic workforce, so if you're excited about this role but your previous experience doesn't align perfectly with every qualification, we encourage you to apply anyway! You may be the perfect candidate for this or another role at May. Want to learn more about our culture & benefits? Check out our website! May Mobility is an equal opportunity employer. All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, veteran status, genetics or any other legally protected basis. Below, you have the opportunity to share your preferred gender pronouns, gender, ethnicity, and veteran status with May Mobility to help us identify areas of improvement in our hiring and recruitment processes. Completion of these questions is entirely voluntary. Any information you choose to provide will be kept confidential, and will not impact the hiring decision in any way. If you believe that you will need any type of accommodation, please let us know. Note to Recruitment Agencies: May Mobility does not accept unsolicited agency resumes. Furthermore, May Mobility does not pay placement fees for candidates submitted by any agency other than its approved partners. Salary Range$167,000-$190,000 USD

Welcome to Perennial. Perennial is building the world's leading verification platform for soil-based carbon removal. Our vision is to unlock soil as one of the world's largest carbon sinks. To do that, we are building trusted standards, tools, and technologies to help verify climate-smart agriculture. Perennial uses advanced remote measurement technology for soil carbon sequestration and emissions. We fuse machine learning, ground observations, and satellite data to map soil carbon and land-based GHG emissions at continent-level scales. This technology is powering the future of climate-smart agriculture and helping the food supply chain decarbonize. At Perennial, you will work in a mission-driven and collaborative environment alongside a diverse team with backgrounds spanning science, technology, carbon markets, and agriculture. Our headquarters is located in Boulder, CO USA. We are a fully-flexible company for remote and hybrid work. We're venture-backed by mission-aligned investors including Temasek, Bloomberg, Microsoft Climate Innovation Fund, SineWave Ventures, Alumni Ventures Group, and Collaborative Fund.Position Overview As a Data Scientist, you will be responsible for algorithm and methodology development for an innovative company using machine learning and remote sensing data to quantify the benefits of regenerative agriculture at scale. The Perennial team is advancing the field of digital soil mapping (DSM) through impactful applied research, peer-reviewed science, and methodology development to bring DSM into the voluntary carbon markets (see our work with Verra). You will help us quantify changes in soil organic carbon stocks in agricultural soils, deliver reliable results for our customers, and partner with our applied scientists and engineers to continually improve our models and processes that support a variety of carbon offset and Scope 3 projects. What You'll Own Build, improve, and deploy machine learning models for predicting soil carbon stock with remotely-sensed covariate data and limited training data End-to-end deliveries for our customers: train models, run predictions, and ensure quality results are delivered in customer reports Work with other data scientists, engineers, and policy experts to ensure that our data and methods comply with various standards and methodology requirements specific to a given project Characterize the accuracy and uncertainty of model predictions and demonstrate the dependence of performance metrics on the surrounding context and parameters of carbon projects Execute efficiently throughout full development cycle, from performing exploratory data analysis and initial R&D to rapid prototyping and hardening models for production Communicate your research internally and externally through detailed documentation, conference presentations, and peer-reviewed publications What You'll Bring Master's degree or Ph.D. in statistics, math, computer science, remote sensing, AI/ML, ecosystem science, soil science, geography, or a related STEM field 3-6 years of industry or research experience in data science, applied ML, geospatial analysis, or related fields Strong proficiency in Python for data science (e.g. pandas, scikit-learn, xarray, numpy) Experience building machine learning, statistical, or time series models informed by remotely-sensed data or large spatial datasets Good communication and collaboration skills with functional and cross-functional teams Ability to independently manage a project and deliver results What Will Make You Stand Out Experience working in the soil carbon MRV space and familiarity with relevant methodologies and tools (e.g. VM0042, VM0032, VMD0053) Expertise in the open source geospatial python stack. Basic raster and vector operations, e.g. resampling, tiling, clipping, extracting, spatial statistics, harmonizing data Experience quantifying uncertainty of spatial maps, or more generally geostatistics or spatial stats, esp. with machine learning Experience working with Google Earth Engine and GCS Startup experience or a strong entrepreneurial mindset (generally private company experience) Why You'll Love Working Here We live by our Core Values. Speak your truths, welcome new voices. Celebrate your successes, own your mistakes. Solve important problems. Invest in each other. Build for the future .Get your hands dirty! We challenge the status quo. We're a group of people who want to create the changes we hope to see in the world. See some of our recent press about the problems we're committed to solving. We invest in your life. We want to provide you with resources to meet your needs both in and outside of work. We offer generous PTO, health, vision, dental, 401k, and HSA benefits and a fully stocked kitchen to keep your mind sharp throughout the day. We want you to grow. We are a team that supports each others' professional and intellectual growth. You'll have access to regular opportunities to learn from teammates and invest in your professional development. We offer competitive compensation packages. Our team is our most valuable asset. We want everyone who works for us to feel fairly compensated for the impact they bring to our mission. The team member in this role can expect a starting salary in the range of USD $120,000-$145,000 (commensurate with experience and location), along with equity in the company. Perennial is an equal opportunity employer. We celebrate and embrace diversity and are committed to building a team that represents a variety of experiences, backgrounds, and skills. We do not discriminate on the basis of race, color, religion, marital status, age, gender identity, gender expression, sexual orientation, non-disqualifying physical or mental disability, national origin, veteran status, or other applicable legally protected characteristics.

Role Description We're looking for a Staff Data Scientist to partner with product, engineering, and design teams to answer key questions and drive impact in the Core Experience and Artificial Intelligence (AI) areas. This area focuses on improving key part of the core product through re-envisioning the home experience, cross platform experience, user onboarding, and building new functionality and launching high impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle, behavior analysis, and customer segmentation. We're looking for someone who can bring opinions and strong narrative framing to proactively influence the business. Responsibilities Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. Identify opportunities, advocate for new solutions and build momentum cross-functionally to move ideas forward tha tare grounded in data. Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments Translate complex concepts into implications for the business via excellent communication skills, both verbal and written Understand what matters most and prioritize ruthlessly Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate Requirements Bachelors' or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field 8+ years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction Significant experience with SQL Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees Solid background in running multivariate experiments to optimize a product or revenue flow Strong verbal and written communication skills Strong leadership and influence skills Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus Preferred Qualifications Product analytics experience in a SAAS company Masters' or above in a quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field Compensation US Zone 1 This role is not available in Zone 1 US Zone 2$197,400-$267,000 USDUS Zone 3$175,400-$237,400 USD

Join the Tilt team At Tilt (formerly Empower), we see a side of people that traditional lenders miss. Our mobile-first products and machine learning-powered credit models look beyond outdated credit scores, using over 250 real-time financial signals to recognize real potential. Named among the next billion-dollar startups, we're not just changing how people access financial products - we're creating a new credit system that backs the working, whatever they're working toward. The Opportunity: Staff Data Scientist Our data scientists are responsible for the entire machine learning model development process from conception with stakeholders, creation of model pipelines, technical development, deployment, and partnership with the credit, product, and finance teams to make business decisions. The ideal candidate is passionate about using data and models to drive business growth and help customers improve their financial situations. For this role, we're looking for a seasoned data scientist to work within our talented DS team for Tilt Cash Advance and Thrive Line of Credit products. This individual will own creating and improving credit risk models, building ML based paycheck detection algorithms to help the business decrease loss rates and increase approval rates. The right person for this role is someone who shines while solving complex problems and is comfortable with a wide variety of technical tools. Tilt is a remote-first company. We drive connectivity through regular company offsites. Travel for company offsites is expected at a minimum 2 times a year. How You'll Make an Impact Grow user base and increase retention through machine learning and analytics Build machine learning models with large scale data sets to address business priorities Design and influence strategies on underwriting, marketing, fraud and customer experience Work closely with our engineering team as you implement models in production Collaborate effectively with operations and product to ensure the work fits into the broader strategy and business context Develop data standards and analytics pipelines to facilitate current and future analysis Why You're a Great Fit BS degree in engineering, computer science, finance or mathematics 6+ years industry experience in data mining, machine learning, statistical analysis, and/or predictive modeling Deep understanding of statistics and machine learning techniques, including regression, classification, clustering and optimization Experience building predictive models from scratch Strong programming skills in Python with intermediate to advanced knowledge of SQL Demonstrable experience with ML packages: scikit-learn, LightGBM, XGBoost, SparkML, etc. Knowledge in deep learning and experience with DL toolkits (Tensorflow, Keras, PyTorch) is preferred though not required Comfort working with a variety of cross functional partners in tech, product, credit, and business Exceptionally strong problem solving and communication with the ability to both get in the weeds and communicate to an executive audience Don't meet every qualification? We care about potential over your past. If you're bringing ambition and drive to what we're building, we want to hear from you. What you'll get at Tilt Virtual-first teamwork: The Tilt team is collaborating across 14 countries, 12 time zones, and counting. You'll get started with a WFH office reimbursement. Competitive pay: We're big on potential, and it's reflected in our competitive compensation packages and generous equity. Complete support: Find flexible health plans at every premium level, and substantial subsidies that stand up to global standards. Visibility is yours: You can count on direct exposure to our leadership team - we're a team where good ideas travel quickly. Paid global onsites: Magic happens IRL: we gather twice yearly to reconnect over shared meals or kayaking adventures. (We've visited Vail, San Diego, and Mexico City, to name a few.) Impact is recognized: Growth opportunities follow your contributions, not rigid promotion timelines. The Tilt Way We're looking for people who chase excellence and impact. Those who stand behind their work, celebrating the wins and learning from the missteps equally. We foster an environment where every voice is valued and mutual respect is non-negotiable - brilliant jerks need not apply. We're in this together, working to expand access to fair credit and prove that people are incredible. When you join us, it's not just another day at the [virtual] office, you're helping millions of hardworking people reach better financial futures. You're pushing ahead in your career? We can get behind that. Join us in building the credit system that people deserve.

#TeamNextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 340,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com. Meet Your Future Neighbors As a Data Scientist 4 at Nextdoor, you'll apply statistical methods, machine learning, and quantitative analysis to conduct exploratory analysis, develop predictive models, and inform operational strategies. In this role, you'll apply data mining and data modeling to extract and analyze information from large structured and unstructured datasets. At Nextdoor, we offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The Impact You'll Make If you want the challenge of fast-paced growth, the satisfaction of seeing your design work come to life, and the pride in helping grow a world-class design team, this is the place for you. Your responsibilities will include: Collect, organize, interpret, and analyze statistical and behavioral data to support the design, improvement and scaling of Company's core products Develop and execute A/B tests and other experimentation frameworks to evaluate the impact of product changes on key metrics such as engagement and retention Communicate insights through advanced data visualization to influence strategic decision-making and product roadmaps Conduct causal inference studies to deeply understand Company's user behavior, engagement patterns, dynamics of local communities, and acquisition pattern Build scalable data solutions, including Extract, Transform, Load (ETL) pipeline and distributed data systems, to process and analyze large and complex datasets efficiently Partner with cross-functional teams (including Product, Engineering and User Experience Research teams) to identify opportunities, solve complex problems, and inform the development of features that foster meaningful neighbor-to-neighbor connections What You'll Bring To The Team Master's degree or foreign equivalent in Computer Science, Information Systems, Engineering, or closely related quantitative discipline 3 years of experience in the position offered, as a Data Scientist, or closely related position in data sciences In the alternative, will accept a Bachelor's degree in the fields above followed by five (5) years of progressive, post-bachelor's experience in positions specified above Must have experience in the following: Utilizing advanced statistical methods and quantitative techniques such as clustering, regression, pattern recognition, and inferential statistics to conduct exploratory analysis, develop and improve predictive models, and provide actionable recommendations to optimize product initiatives and generate data-driven business strategies; Leveraging Python, SQL and statistical tools such as MATLAB, R, and SAS to analyze large, complex datasets through data mining, manipulation, analysis, and modeling, ensuring data reliability to drive business growth; Designing trustworthy experimentation and analyzing complex product A/B testing results to evaluate the effectiveness of product strategies and provide data-driven insights to guide decision-making; Designing, constructing, and deploying scalable ETL (extraction, transformation, and loading) pipelines and data processing frameworks to develop metrics and dashboards that drive data-informed product strategy; Leading the execution of key ecosystem strategies, including developing new capabilities like customer segment frameworks, to drive growth and optimize product performance; Utilizing advanced data analysis to generate strategic insights, assessing product team performance and impact to inform decision-making and guide improvements; Collaborating with cross-functional teams (product, design, engineering, marketing, and operations) to apply advanced analytics in support of product development, ensuring alignment with business goals; and Utilizing strong communication skills to simplify complex problems and present clear, compelling narratives to diverse audiences, including executives Rewards Compensation, benefits, perks, and recognition programs at Nextdoor come together to create our total rewards package. Compensation will vary depending on your relevant skills, experience, and qualifications. Compensation may also vary by geography. The starting salary for this role is expected to range from $214,000 - $225,000/year on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. We expect to award a meaningful equity grant for this role. With quarterly vesting, your first vest date will take place within 3 months of your start date. When it comes to benefits, we have you covered! Nextdoor employees can choose between a variety of health plans, including a 100% covered employee only plan option, and we also provide a OneMedical membership for concierge care. At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we serve. We encourage everyone interested in our mission to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records. For information about our collection and use of applicants' personal information, please see Nextdoor's Personnel Privacy Notice, found here. #LI-DNI

Who are we? Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008. Summary As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh, you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM) solutions that power next-generation compliance and surveillance systems. You'll work on highly specialized problems at the intersection of natural language processing, communications intelligence, financial supervision, and regulatory compliance, where unstructured data from emails, chats, voice transcripts, and trade communications hold the keys to uncovering misconduct and risk. The role will involve working with other Senior Data Scientists and mentoring Associate Data Scientists in analyzing complex data, generating insights, and creating solutions as needed across a variety of tools and platforms. This role demands both technical excellence in NLP modeling and a deep understanding of financial domain behavior-including insider trading, market manipulation, off-channel communications, MNPI, bribery, and other supervisory risk areas. The ideal candidate for this position will possess the ability to perform both independent and team-based research and generate insights from large data sets with a hands-on/can do attitude of servicing/managing day to day data requests and analysis. This role also offers a unique opportunity to get exposure to many problems and solutions associated with taking machine learning and analytics research to production. On any given day, you will have the opportunity to interface with business leaders, machine learning researchers, data engineers, platform engineers, data scientists and many more, enabling you to level up in true end-to-end data science proficiency.How will you contribute? Collect, analyze, and interpret small/large datasets to uncover meaningful insights to support the development of statistical methods / machine learning algorithms. Lead the design, training, and deployment of NLP and transformer-based models for financial surveillance and supervisory use cases (e.g., misconduct detection, market abuse, trade manipulation, insider communication). Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities Data annotation and quality review Exploratory data analysis and model fail state analysis Contribute to model governance, documentation, and explainability frameworks aligned with internal and regulatory AI standards. Client/prospect guidance in machine learning model and analytic fine-tuning/development processes Provide guidance to junior team members on model development and EDA Work with Product Manager(s) to intake project/product requirements and translate these to technical tasks within the team's tooling, technique and procedures Continued self-led personal development What will you bring? Strong understanding of financial markets, compliance, surveillance, supervision, or regulatory technology Experience with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc…) Strong knowledge of key programming concepts (e.g. split-apply-combine, data structures, object-oriented programming) Solid statistics knowledge (hypothesis testing, ANOVA, chi-square tests, etc…) Knowledge of NLP transfer learning, including word embedding models (glo Ve, fast Text, word2vec) and transformer models (Bert, SBert, HuggingFace, and GPT-x etc.) Experience with natural language processing toolkits like NLTK, spa Cy, Nvidia NeMo Knowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and Kubernetes Familiarity with Deep Learning techniques for NLP. Familiarity with LLMs - using ollama & Langchain Excellent verbal and written skills Proven collaborator, thriving on teamwork Preferred Qualifications Master's or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field Familiarity with cloud computing platforms (AWS, GCS, Azure) Experience with automated supervision/surveillance/compliance tools About our culture Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world's leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible. What you'll do Be the technical lead for the forecasting team. Own the strategy and implementation of forecasting models of key company metrics (e.g., monthly active users), delivering accurate, interpretable forecasts at scale. Lead the full modeling lifecycle end to end: problem framing, feature engineering, model development and prototyping, experimentation and backtesting, deployment, monitoring/drift detection, and explainability. Set the forecasting technical vision. Define model architectures and standards, and partner with Engineering to shape the forecasting platform for efficient training/inference today and the scalability needed for the next generation of models. Translate forecasts into decisions. Present outputs, scenario analyses, and recommendation frameworks to senior leadership with clarity and brevity. This is a high‑visibility role with regular VP-level exposure. Drive broader time‑series impact beyond point forecasts-e.g., anomaly detection, automated root‑cause analysis, campaign/channel attribution, and early‑warning signals for business health. Embed forecasting into the business. Partner with BizOps/Finance and product teams to integrate forecasts and insights into operational rhythms, executive decision-making, and strategic planning. Lead and mentor. Guide the work of at least two data scientists, raising the bar on technical quality, execution, and impact through candid, continuous feedback and coaching. What we're looking for 8+ years of combined post-graduate academic and industry experience building and shipping production time‑series/forecasting models with web‑scale data. A track record of delivering adjustable, well‑calibrated, and explainable forecasting systems that informing decision-making. Strong background in time‑series modeling and applied statistics/econometrics; advanced degree (MS or PhD) preferred. Expertise in at least one scripting language (ideally Python). Strong SQL skills (Hive/Presto/Spark SQL) and experience building reliable data pipelines/workflows (e.g., Airflow). Business acumen and ownership mindset-able to simplify complex problems, connect model outputs to business levers, and prioritize for impact. Excellent communication skills-able to distill complex analyses and uncertainty into concise narratives for executive audiences. Proven technical leadership-success leading critical projects and materially influencing the scope and output of other contributors. Relocation Statement: This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. In-Office Requirement Statement: We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection. This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country. #LI-NM4 #LI-REMOTE At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. Information regarding the culture at Pinterest and benefits available for this position can be found here. US based applicants only$164,695-$339,078 USD Our Commitment to Inclusion: Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.

National Debt Relief (NDR) is seeking an experienced and versatile Data Scientist IV (Principal level) to join our Data Science team and round out our capabilities. This is a principal-level role for a highly skilled individual contributor with a minimum of 7+ years of proven experience in building and deploying enterprise-grade production machine learning (ML) and artificial intelligence (AI) models. This is a highly collaborative role, and strong teamwork and interpersonal skills are required. As a subject matter expert, you will augment the team's existing strengths in all industry-standard data science models, tools, and model deployment technologies. Deep familiarity with the data science model lifecycle and model deployment tools is essential. This individual will be pivotal in enhancing the team's capacity to conceptualize, develop, and deploy complex models efficiently and on time. Responsibilities Serve as a strategic addition to the data science team, contributing advanced technical expertise to complement existing skills. Conceptualize, develop, and deploy production-grade ML models and AI applications, consistently delivering projects within 8-12 week timeframes. Apply sophisticated data science techniques, including unsupervised learning, clustering, time series analysis, anomaly detection, NLP, topic modeling, and generative AI, to address business Implement and maintain MLOps practices to streamline and manage the full model lifecycle for scalable, production-ready solutions. Develop and deploy models as APIs using frameworks such as FastAPI or Docker for efficient integration into production systems. Collaborate with cross-functional teams to identify business needs and translate them into impactful data science solutions. Use strong SQL (Snowflake preferred) and Python skills for data preparation, analysis, and model Demonstrate high business acumen by understanding the practical implications of data science projects and communicating effectively with stakeholders. Present complex analyses and results to both technical and non-technical audiences, ensuring clarity and actionable insights. Provide technical guidance and share expertise with peers and junior data scientists, contributing to a culture of continuous learning and innovation. Qualifications Education/Experience Bachelor's degree in Data Science, Computer Science, Statistics, or a related field required. A master's or Ph.D. is preferred. 7+ years of professional, full-time data science experience with a proven track record of developing and deploying production-grade ML models. Advanced proficiency in Python and SQL (Snowflake preferred), with significant hands-on experience building highly performant code. Deep expertise in MLOps and experience managing production model workflows. Strong experience developing and deploying ML models as APIs using tools such as FastAPI, Docker, or similar frameworks is highly preferred. Proven application of advanced data science techniques beyond classification and regression, including unsupervised learning, clustering, time series analysis, anomaly detection, NLP, topic modeling, and generative AI. Demonstrated ability to develop and deploy models on time, with examples of successful implementations. Exceptional communication skills for explaining complex data insights to diverse audiences. Ability to foster a culture of collaboration, continuous improvement, and innovation. Required Skills/Abilities Experience in financial services or a related industry. Experience with data warehouse solutions such as Snowflake (preferred), Azure, Redshift, or GCP. Familiarity with data visualization tools for impactful presentations. Exposure to collaborative tools such as JIRA and Miro. National Debt Relief Role Qualifications: Computer competency and ability to work with a computer. Prioritize multiple tasks and projects simultaneously. Exceptional written and verbal communication skills. Punctuality expected, ready to report to work on a consistent basis. Attain and maintain high performance expectations on a monthly basis. Work in a fast-paced, high-volume setting. Use and navigate multiple computer systems with exceptional multi-tasking skills. Remain calm and professional during difficult discussions. Take constructive feedback. Available for full-time position, overtime eligible if classified non-exempt. Compensation Information Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for each position across the US. Within the range, individual pay is determined by work location, job-related skills, experience, and relevant education or training. This good faith pay range is provided in compliance with NYC law and the laws of other jurisdictions that may require a salary range in job postings. The salary for this position is $176,000 - $202,500 annually. About National Debt Relief National Debt Relief was founded in 2009 with the goal of helping an expanding number of consumers deal with overwhelming debt. We are one of the most-trusted and best-rated consumer debt relief providers in the United States. As a leading debt settlement organization, we have helped over 450,000 people settle over $10 billion of debt, while empowering them to lead a healthier financial lifestyle and feel free to live their best life. At National Debt Relief, we treat our clients like real people. Our purpose is to elevate, empower, and transform their lives. Rated A+ by the Better Business Bureau, our goal is to help individuals and families get out of debt with the least possible cost through conducting financial consultations, educating the consumer and recommending the appropriate solution. We become our clients' number one advocate to help them reestablish financial stability as quickly as possible. Benefits National Debt Relief is a team-oriented environment full of rewards and growth opportunities for our employees. We are dedicated to our employee's success and growth within the company, through our employee mentorship and leadership programs. Our extensive benefits package includes: Generous Medical, Dental, and Vision Benefits 401(k) with Company Match Paid Holidays, Volunteer Time Off, Sick Days, and Vacation 12 weeks Paid Parental Leave Pre-tax Transit Benefits No-Cost Life Insurance Benefits Voluntary Benefits Options ASPCA Pet Health Insurance Discount Access to your earned wages at any time before payday National Debt Relief is a certified Great Place to Work ! National Debt Relief is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other status protected by law. For information about our Employee Privacy Policy, please see here For information about our Applicant Terms, please see here #LI-REMOTE

**Dean of Research, Stanford, California, United States** Research Post Date Dec 13, 2024 Requisition # 105424 This is a 3-year fixed term appointment. **Stanford Data Science** This position is part of a new initiative incubated within Stanford Data Science, part of the Vice Provost for Research / Dean of Research. Stanford Data Science (SDS) is a dynamic and rapidly growing unit within the VP/Dean of Research. For more than five years, SDS has sought to advance data science and its application to all fields of study. Our community ranges broadly across all seven schools on campus, consisting of esteemed alumni, world class faculty, post-doctoral fellows and PhD students, dynamic staff and administrators. In realizing our mission, our staff are critical to supporting our organization's goals and enabling Stanford faculty and students to accomplish their mission conducting cutting-edge research and innovation around how we learn from data, the tools we use, and the new methods needed to tackle the data-intensive future. **POSITION SUMMARY** Stanford University has made a strategic investment in Marlowe, a GPU-centric high-performance computing instrument designed to enable large-scale, data-intensive research. Supporting a wide range of disciplines, Marlowe facilitates sophisticated machine learning applications, including large-language models. The Research Data Scientist will play a critical role in this initiative, leveraging their expertise in computational research to develop and optimize workflows and applications that unlock Marlowe's capabilities. This role requires a deep understanding of computational and data science, machine learning, and the scientific process. It also demands the ability to leverage high-performance GPU computing to efficiently process and analyze large datasets. The successful candidate will collaborate closely with Stanford faculty and research groups to design, implement, and refine GPU-accelerated data processing pipelines. They will also contribute to scientific codes using machine learning, statistical analysis, and computation to address complex research challenges. Additionally, the data scientist will contribute to the development of novel computational methods ranging from biological data analysis to simulation of physical systems via digital twins. Beyond technical expertise, the Research Data Scientist will act as a bridge between Marlowe and the broader research community. They will guide researchers in adapting their applications to Marlowe's GPU-powered infrastructure by providing technical consultation, creating training materials, and leading workshops. The ideal candidate will have a strong background in both data science and GPU-centric computational techniques, combined with a passion for fostering collaboration and pushing the boundaries of interdisciplinary research. This position offers an exceptional opportunity to drive transformational research and establish Marlowe as a cornerstone of Stanford's efforts in pioneering discovery. Remote work for the Research Data Scientist position will be considered. The Research Data Scientist may be asked to attend certain in-person work events during the year regardless of remote status. **CORE DUTIES** **:** **Code Architecture for GPU Computation** + Collaborate with Principal Investigators (PIs) and research groups to architect and optimize GPU-accelerated pipelines. + Develop innovative computational methodologies + Co-author resulting research publications. **Algorithm Development and Data Management** + Design advanced data movement strategies to minimize memory bottlenecks between CPU and GPU, including real-time data streaming methods for scientific applications. + Partner with research teams to design novel algorithms and develop high-quality, reusable software to accelerate complex research projects. **Research Support and Software Infrastructure** + Assist PIs in applying for supercomputing resources at national centers once projects are scaled and workloads are appropriate. Offer guidance on maximizing efficiency of large-scale computational experiments. + Install, configure, and maintain software stacks for core research functions. **Training and Mentorship** + Design and lead hands-on workshops, and interdisciplinary courses focused on GPU-centric research in fields such as computational biology, NLP and image analysis. + Mentor graduate students, postdocs and early-career researchers in computational techniques and research methodologies. **Open Science and Research Continuity** + Integrate open science principles into research workflows, including software for data and computational provenance. + Design systems to manage inputs, outputs, and provenance to meet NIH, NSF, and OSTP mandates. + Develop tools and workflows to ensure the long-term viability of code and tools used by students and postdocs for future research development. *Other duties as assigned. **DESIRED QUALIFICATIONS** **:** + Experience supervising technical staff including training, mentoring and coaching. + Experience developing and writing grant proposals. + A minimum of five years at an Academic Staff - Researcher rank or have equivalent experience + Extensive publication list including first author publications. **Education & Experience (Required)** : + Ph.D. in a computational or data-intensive related field or equivalent + Comfortable running and troubleshooting jobs in a batch scheduled environment + Considerable experience with Linux **Pay Range** **:** This role is open to candidates anywhere in the United States. Stanford University hasfive Regional Pay Structures. The compensation for this position will be based on the location of the successful candidate. The expected pay range for this position is $142,000 to $200,000 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location, and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website (***************************************************** provides detailed information on Stanford's extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process. _The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned._ _Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources by submitting a contact form._ _Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law._ Additional Information + **Schedule: Full-time** + **Job Code: 6446** + **Employee Status: Fixed-Term** + **Grade: R99** + **Requisition ID: 105424** + **Work Arrangement : Hybrid Eligible, Remote Eligible, On Site**

The Program Integrity Data Scientist II is responsible for developing, implementing, managing, and deploying in-depth analyses that meet the information needs associated with payment accuracy, anomaly detection, and Fraud, Waste, and Abuse (FWA). Essential Functions: Build concepts as algorithms that identify claims for pre- or post-pay intervention based on probability of fraud, waste, and abuse. Algorithms are implemented into production workflows for action: medical record request and audit, downcode adjustment, denial and remittance communication, etc. Analyze and quantify claim payment issues and provide recommendations to mitigate identified program integrity risks. Identify trends and patterns using standard corporate, processes, tools, reports and databases as well as leveraging other processes and data sources. Conduct outcome analyses to determine impact and effectiveness of corporate program and payment integrity initiatives. Collaborate on the examination and explanation of complex data relationships to answer questions identified either within the department or by other departments as it relates to payment accuracy, anomaly detection, and FWA. Monitoring of and providing explanation of anomalies related to trends associated with the potential for Fraud Waste and Abuse across the corporate enterprise. Collaborate with the Legal Department, generating data and analyses to support Legal proceedings. Develop hypothesis tests and extrapolations on statistically valid samples to establish outlier behavior patterns and potential recoupment. Create, maintain, and communicate an analytical plan for each project. Mine and analyze large structured and unstructured datasets. Employ wide range of data sources to develop algorithms for predicting risk and understanding drivers, detecting outliers, etc. Develop visualizations that demonstrate the efficacy of developed algorithms. Provide statistical validation and analysis of outcomes associated with clinical programs and interventions. Collaborate with other teams to integrate with existing solutions. Communicate results and ideas to key stakeholders. Prepare code for operationalization of end-to-end model pipeline and deliverable for business consumption. Perform any other job related duties as requested. Education and Experience: Bachelor's degree in Data Science, Mathematics, Statistics, Engineering, Computer Science, or a related field required Equivalent years of relevant work experience may be accepted in lieu of required education Three (3) years data analysis and/or analytic programming required Experience with cloud services (such as Azure, AWS or GCP) and modern data stack (such as Databricks or Snowflakes) preferred Healthcare experience required Competencies, Knowledge and Skills: Proficient in SQL and at least one of the following programming languages: Python / R / RAT STAT Familiarity with SAS is preferred Preferred beginner level of knowledge of developing reports or dashboards in Power BI or other business intelligence applications Ability to perform advanced statistical analyses and techniques including t-tests, ANOVAs, z-tests, statistical extrapolations, non-parametric significance testing, and sampling methodologies Working knowledge of predictive modeling and machine learning algorithms such as generalized linear models, non-linear supervised learning models, clustering, decision trees, dimensionality reduction and natural language processing Proficient in feature engineering techniques and exploratory data analysis Familiarity with optimization techniques and artificial intelligence methods Ability to analyze large quantities of information and identify patterns, irregularities, and deficiencies Knowledge of healthcare coding and billing processes, including CPT4, HCPCS, ICD-9, DRG and Revenue Codes preferred Proficient with MS office (Excel, PowerPoint, Word, Access) Demonstrated critical thinking, verbal communication, presentation and written communication skills Ability to work independently and within a cross-functional team environment Licensure and Certification:Working Conditions: General office environment; may be required to sit or stand for extended periods of time Up to 15% (occasional) travel to attend meetings, trainings, and conferences may be required Compensation Range: $81,400.00 - $130,200.00 CareSource takes into consideration a combination of a candidate's education, training, and experience as well as the position's scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee's total well-being and offer a substantial and comprehensive total rewards package. Compensation Type (hourly/salary): Salary Organization Level Competencies Fostering a Collaborative Workplace Culture Cultivate Partnerships Develop Self and Others Drive Execution Influence Others Pursue Personal Excellence Understand the Business This is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.#LI-GB1

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana's marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design. This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you'll achieve: Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines. Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability. Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach. Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops. Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably. Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation. Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products. About you: Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift) Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness Proven track record developing, deploying, and maintaining scalable production ML solutions and data products Demonstrated curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making. What we'll offer: Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit. For this role, the estimated base salary range is between $202,000 - $316,00. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified. In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role. We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role. #LI-Hybrid #LI-AA1 About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. Join Asana's Talent Network to stay up to date on job opportunities and life at Asana.

Simulation Developer -Data Scientist (Simulation & Modeling) About the Role We are seeking a highly skilled and motivated Data Scientist with expertise in simulation modeling, probability theory, and Python programming. This role focuses on designing and deploying simulation frameworks to evaluate and optimize enterprise solutions. Ideal candidates will have experience in inventory models, stochastic processes, and building scalable simulation systems. Key Responsibilities Design, develop, and deploy simulation models for inventory and operational systems using Python, SQL, and PySpark on platforms like Databricks. Apply probability theory and Monte Carlo methods to model uncertainty and variability. Collaborate with Data Engineers and Data Scientists to define simulation inputs and integrate pipelines. Implement CI/CD principles and manage code repositories using GitHub Enterprise. Validate and calibrate simulation models using historical data and sensitivity analysis. Ensure code quality, scalability, and maintainability in production environments. Required Qualifications Hands-on experience with simulation modeling and inventory systems. Proficiency in Python, SQL, and PySpark. Strong understanding of probability theory, stochastic modeling, and Monte Carlo simulation. Experience with Databricks or similar enterprise cloud environments. Familiarity with CI/CD principles and GitHub Enterprise. Self-starter with an ownership mindset and ability to work independently. Preferred Qualifications Experience in retail, supply chain, or operations research. Familiarity with cloud platforms (Azure, AWS, GCP).

Porch Group is a leading vertical software and insurance platform and is positioned to be the best partner to help homebuyers move, maintain, and fully protect their homes. We offer differentiated products and services, with homeowners insurance at the center of this relationship. We differentiate and look to win in the massive and growing homeowners insurance opportunity by 1) providing the best services for homebuyers, 2) led by advantaged underwriting in insurance, 3) to protect the whole home. As a leader in the home services software-as-a-service (“SaaS”) space, we've built deep relationships with approximately 30 thousand companies that are key to the home-buying transaction, such as home inspectors, mortgage companies, and title companies. In 2020, Porch Group rang the Nasdaq bell and began trading under the ticker symbol PRCH. We are looking to build a truly great company and are JUST GETTING STARTED. Job Title: Data Scientist, Insurance Risk and Pricing Location: United States Workplace Type: Remote Job Summary The future is bright for the Porch Group, and we'd love for you to be a part of it as our Data Scientist, Insurance Risk and Pricing We are looking for a results-driven Data Scientist to join our high-impact team focused on transforming the insurance and home services industries. You will play a key role in leveraging Porch's unique property data to drive innovation, improve risk understanding, and optimize pricing strategies. This role is ideal for someone who thrives in a fast-paced, data-rich environment and is passionate about delivering measurable business value. What You Will Do As A Data Scientist, Insurance Risk and Pricing Model Development: Build and deploy advanced predictive models that support pricing, retention, and customer satisfaction initiatives. Data Exploration & Analysis: Conduct deep-dive analyses to uncover insights that inform strategic decisions across the business. Cross-Functional Collaboration: Work closely with product, engineering, and business teams to scope projects and integrate data science solutions into operational workflows. Innovation & Impact: Contribute to a culture of experimentation and continuous improvement, stay up to date on new technologies and innovation, identifying new opportunities to apply data science for competitive advantage. What You Will Bring As A Data Scientist, Insurance Risk and Pricing At least 5 years of experience in data science Proficiency in Python and R, and strong SQL skills. Experience building and deploying in high traffic environments Solid understanding of statistical modeling, machine learning, and data wrangling. Experience with cloud-based data platforms (e.g., Snowflake, BigQuery, AWS, GCP). Strong communication skills and the ability to translate complex data into actionable insights. Preferred Experience in insurance pricing and risk quantification Exposure to experimentation frameworks and causal inference methods. Actuarial Certifications ACAS and/or FCAS The application window for this position is anticipated to close in 2 weeks (10 business days) from 10/23/2025 Please know this may change based on business and interviewing needs. At this time, Porch Group does not consider applicants from the following states or jurisdictions for Remote positions: Alaska, Delaware, Hawaii, Iowa, Maine, Mississippi, Montana, New Hampshire, West Virginia, or the District of Columbia. What You Will Get As A Porch Group Team Member Pay Range*: $138,800 - $194,300 *Please know your actual pay at Porch will reflect a number of factors among which are your work experience and skillsets, job-related knowledge, alignment with market and our Porch employees, as well as your geographic location. Additionally, you will be eligible to receive long-term incentive awards, subject to program guidelines and approvals. Our benefits package will provide you with comprehensive coverage for your health, life, and financial wellbeing. Our traditional healthcare benefits include three (3) Medical plan options, two (2) Dental plan options, and a Vision plan from which to choose. Critical Illness, Hospital Indemnity and Accident plans are offered on a voluntary basis. We offer pre-tax savings options including a partially employer funded Health Savings Account and employee Flexible Savings Accounts including healthcare, dependent care, and transportation savings options. We provide company paid Basic Life and AD&D, Short and Long-Term Disability benefits. We also offer Voluntary Life and AD&D plans. Both traditional and Roth 401(k) plans are available with a discretionary employer match. Supportlinc is part of our employer paid wellbeing program and provides employees and their families access to on demand guided meditation and mindfulness exercises, mental health coaching, clinical care and online access to confidential resources including will preparation. LifeBalance is a free resource to employees and their families for year-round discounts on things like gym memberships, travel, appliances, movies, pet insurance and more. Our wellness programs include flexible paid vacation, company-paid holidays of typically nine per year, paid sick time, paid parental leave, identity theft program, travel assistance, and fitness and other discounts programs. #LI-NH1 What's next? Submit your application and our Porch Group Talent Acquisition team will be reviewing your application shortly! If your resume gets us intrigued, we will look to connect with you for a chat to learn more about your background, and then possibly invite you to have virtual interviews. What's important to call out is that we want to make sure not only that you're the right person for us, but also that we're the right next step for you, so come prepared with all the questions you have! Porch is committed to building an inclusive culture of belonging that not only embraces the diversity of our people but also reflects the diversity of the communities in which we work and the customers we serve. We know that the happiest and highest performing teams include people with diverse perspectives that encourage new ways of solving problems, so we strive to attract and develop talent from all backgrounds and create workplaces where everyone feels seen, heard and empowered to bring their full, authentic selves to work. Porch is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex including sexual orientation and gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable laws, regulations, and ordinances. Porch Group is an E-Verify employer. E-Verify is a web-based system that allows an employer to determine an employee's eligibility to work in the US using information reported on an employee's Form I-9. The E-Verify system confirms eligibility with both the Social Security Administration (SSA) and Department of Homeland Security (DHS). For more information, please go to the USCIS E-Verify website.

The Data Scientist will contribute to the development of AI and Generative AI (GenAI) models and workflows tailored for the healthcare domain. This role will work on building solutions that address real-world challenges. This role offers an exciting opportunity to apply knowledge of GenAI, machine learning, and healthcare-specific requirements while collaborating with a multidisciplinary team of experts. Develop workflows to enhance the efficiency and accuracy of note-taking in healthcare settings. Collaborate with data engineers, product teams, and clinical experts to ensure solutions align with healthcare workflows and standards. Address healthcare-specific challenges such as HIPAA compliance, medical terminology integration, and adherence to standards like ICD, CPT, and HL7/FHIR. Stay updated with the latest advancements in GenAI, NLP, computer vision, and healthcare AI technologies. Perform other duties that support the overall objective of the position. Education Required: Bachelor's degree (or higher) in Computer Science, Data Science, Artificial Intelligence, or a related field. Or, any combination of education and experience which would provide the required qualifications for the position. Experience Required: Experience working with multiple GenAI models, including open-source. Experience with natural language processing (NLP) and computer vision techniques. Experience in data preprocessing and model deployment. Knowledge, Skills & Abilities: Knowledge of: Strong foundational knowledge of generative AI techniques and frameworks (e.g., Transformers, GPT, diffusion models). Proficiency in machine learning tools and frameworks such as TensorFlow, PyTorch, or Scikit-learn. Familiarity with healthcare data structures, workflows, and challenges (e.g., EMR/EHR integration, ICD/CPT coding, HL7/FHIR). Knowledge of voice recognition and transcription technologies is a plus. Skill in: Strong programming skills in Python or similar languages. Strong problem-solving skills and a growth mindset. Ability to: Eagerness to learn and adapt in a fast-paced, mission-driven environment. The company has reviewed this to ensure that essential functions and basic duties have been included. It is intended to provide guidelines for job expectations and the employee's ability to perform the position described. It is not intended to be construed as an exhaustive list of all functions, responsibilities, skills and abilities. Additional functions and requirements may be assigned by supervisors as deemed appropriate. This document does not represent a contract of employment, and the company reserves the right to change this job description and/or assign tasks for the employee to perform, as the company may deem appropriate. NextGen Healthcare is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

The Data Scientist will provide meaningful insight on how to improve our current business operations. Principle Accountabilities/Responsibilities Work closely with domain experts and SME's to understand the business problem or opportunity and assess the potential of machine learning to enable accelerated performance improvements Design, build, tune, and deploy divisional AI/ML tools that meet the agreed upon functional and non-functional requirements within the framework established by the Enterprise IT and IS departments. Perform large scale experimentation to identify hidden relationships between different data sets and engineer new features Communicate model performance & results & tradeoffs to stake holders Determine requirements that will be used to train and evolve deep learning models and algorithms Visualize information and develop engaging dashboards on the results of data analysis. Build reports and advanced dashboards to tell stories with the data. Lead, develop and deliver divisional strategies to demonstrate the: what, why and how of delivering AI/ML business outcomes Build and deploy divisional AI strategy and roadmaps that enable long-term success for the organization that aligned with the Enterprise AI strategy. Proactively mine data to identify trends and patterns and generate insights for business units and management. Mentor other stakeholders to grow in their expertise, particularly in AI / ML, and taking an active leadership role in divisional executive forums Work collaboratively with the business to maximize the probability of success of AI projects and initiatives. Identify technical areas for improvement and present detailed business cases for improvements or new areas of opportunities. Qualifications/Education/Experience Requirements PhD or master's degree in Statistics, Mathematics, Computer Science or other relevant discipline. 5+ years of experience using large scale data to solve problems and answer questions. Prior experience in the Manufacturing Industry. Skills/Competencies Requirements Experience in building and deploying predictive models and scalable data pipelines Demonstrable experience with common data science toolkits, such as Python, PySpark, R, Weka, NumPy, Pandas, scikit-learn, SpaCy/Gensim/NLTK etc. Knowledge of data warehousing concepts like ETL, dimensional modeling, and sematic/reporting layer design. Knowledge of emerging technologies such as columnar and NoSQL databases, predictive analytics, and unstructured data. Fluency in data science, analytics tools, and a selection of machine learning methods - Clustering, Regression, Decision Trees, Time Series Analysis, Natural Language Processing. Strong problem solving and decision-making skills Ability to explain deep technical information to non-technical parties Demonstrated growth mindset, enthusiastic about learning new technologies quickly and applying the gained knowledge to address business problems. Strong understanding of data governance/management concepts and practices. Strong background in systems development, including an understanding of project management methodologies and the development lifecycle. Proven history managing stakeholder relationships. Business case development. First Quality is committed to protecting information under the care of First Quality Enterprises commensurate with leading industry standards and applicable regulations. As such, First Quality provides at least annual training regarding data privacy and security to employees who, as a result of their role specifications, may come in to contact with sensitive data. First Quality is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, sexual orientation, gender identification, or protected Veteran status.