Data science internship jobs in Indio, CA - 2,093 jobs

A leading audio entertainment service is seeking a Research Scientist to analyze marketing campaign effectiveness through causal models and experimental studies. This role involves collaborating with marketing teams and utilizing advanced statistical methods to enhance decisions and strategies. The ideal candidate holds a PhD or a Master's with significant quantitative research experience and proficiency in scripting languages like R or Python. Comprehensive benefits and competitive compensation are offered. #J-18808-Ljbffr

A healthcare solutions company seeks an Analyst in San Francisco. You'll analyze healthcare data, build dashboards, and provide actionable insights to leadership. Ideal candidates have 2+ years in analytical roles and should be proficient in SQL and Excel. This position offers the chance to make a significant impact as the first analyst in a fast-paced environment, with opportunities for growth and innovation in consumer healthcare. #J-18808-Ljbffr

BI Data Analyst (BI Tableau, SQL, Python) **Prefer candidates who can work on W2** (No for C2C arrangements) Onsite in Sunnyvale, CA / Austin, TX / Elk Grove, CA from Day 1 (Client prefer local folks) Hybrid Schedule: 3 Onsite Days (Tue, Wed, Thur) & 2 Remote Days (Mon, Fri) Long term contract Direct client opportunity No mid layer / No Implementation partners are Involved Job Description: Clients focus more on Business Intelligence skills, less complex analysis. Please make sure that candidates have been using Tableau, SQL, and Python on a weekly basis for the past 5+ years Excellent communication is essential Requires working knowledge of probability theory and statistical analysis. This role will: Use Tableau to create visualizations to be used in interactive dashboards and presentations. Use SQL to manipulate and prepare data Use Python to manipulate and prepare data; create visualizations; analyze data. Require a working knowledge of formal statistical analysis and causal modeling. Require excellent communication skills Skill Sets - Experience - Preference Tableau - 5-10 years - Is Required SQL - 5-10 years - Is Required Python - 5-10 years - Is Required Statistical analysis - 5-10 years - Is Required Verbal Communication - 5-10 years - Is Required Written Communication - 5-10 years - Is Required Attention to Detail - 5-10 years - Is Required Pay Range: $65/hr - $70/hr The specific compensation for this position will be determined by a number of factors, including the scope, complexity and location of the role as well as the cost of labor in the market; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits including medical, dental, vision and 401K contributions as well as any other PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global do not respond or click on any links. Instead, contact us directly at ***************. To report any concerns, please email us at *******************

Title: Technical Data Analyst Contract We are seeking a 10+ years' experience Technical Data Analyst with strong expertise in SQL and Python, hands-on experience with modern data platforms, and the ability to translate complex data into trusted, actionable insights. This role will work closely with engineering, product, and business stakeholders to support analytics, reporting, and data-driven decision-making at scale. Key Responsibilities Write complex, high-performance SQL queries to analyze large, structured and semi-structured datasets 8-10 years of software development and deployment experience with at least 5 years of hands-on experience with SQL, Databricks, ADF, Datastage (or other ETL tool), SSAS cubes, Cognos, Tableau, Thoughtspot and other BI tools ·Write SQL for processing raw data, kafka ingestions, adf pipelines, data validation and QA ·Knowledge working with APIs to collect or ingest data Use Python for data analysis, automation, validation, and lightweight data engineering tasks Build, enhance, and maintain dashboards and reports using Tableau and ThoughtSpot Partner with data engineers to design, validate, and optimize ETL/ELT pipelines Work extensively with Databricks (Spark, notebooks, Delta tables) for data exploration and analytics Perform data quality checks, reconciliations, and root-cause analysis to ensure data accuracy and consistency Translate business requirements into technical data solutions and semantic layers Support self-service analytics by documenting datasets, metrics, and business definitions Collaborate across teams to troubleshoot data issues and improve reporting performance Required Qualifications Strong proficiency in SQL, including complex joins, window functions, CTEs, and performance optimization Strong Python skills for data analysis and scripting (e.g., pandas, numpy) Hands-on experience with Databricks and distributed data processing concepts Hands on experience working with ETL tools and data pipelines (batch and/or streaming) Proficiency in reporting and visualization tools such as Tableau, ThoughtSpot, Cognos, SSAS Cubes Solid understanding of data warehousing concepts, data modeling, and analytics best practices Ability to analyze large datasets and communicate insights clearly to both technical and non-technical audiences Preferred Qualifications Experience with cloud data platforms (AWS, Azure, or GCP) Familiarity with version control tools (Git) and CI/CD concepts for analytics workflows Exposure to data governance, metric standardization, and semantic layers Prior experience in enterprise-scale data platforms or COE environments What Success Looks Like Trusted, accurate dashboards and datasets used across multiple business teams Efficient, well-documented SQL and Python code that scales with data growth Strong partnership with engineering and business stakeholders to deliver timely insights Proactive identification and resolution of data quality and performance issues

Salary: $200-250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We're expanding our data science organization to accelerate customer success after the initial sale-driving onboarding, retention, expansion, and long-term revenue growth. About the Role As the senior data scientist supporting post-sales teams, you will use advanced analytics, experimentation, and predictive modeling to guide strategy across Customer Success, Account Management, and Renewals. Your insights will help leadership forecast expansion, reduce churn, and identify the levers that unlock sustainable net revenue retention. Key Responsibilities Forecast & Model Growth: Build predictive models for renewal likelihood, expansion potential, churn risk, and customer health scoring. Optimize the Customer Journey: Analyze onboarding flows, product adoption patterns, and usage signals to improve activation, engagement, and time-to-value. Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of onboarding programs, success initiatives, and pricing changes on retention and expansion. Revenue Insights: Partner with Customer Success and Sales to identify high-value accounts, cross-sell opportunities, and early warning signs of churn. Cross-Functional Partnership: Collaborate with Product, RevOps, Finance, and Marketing to align post-sales strategies with company growth goals. Data Infrastructure Collaboration: Work with Analytics Engineering to define data requirements, maintain data quality, and enable self-serve dashboards for Success and Finance teams. Executive Storytelling: Present clear, actionable recommendations to senior leadership that translate complex analysis into strategic decisions. About You Experience: 6+ years in data science or advanced analytics, with a focus on post-sales, customer success, or retention analytics in a B2B SaaS environment. Technical Skills: Expert SQL and proficiency in Python or R for statistical modeling, forecasting, and machine learning. Domain Knowledge: Deep understanding of SaaS metrics such as net revenue retention (NRR), gross churn, expansion ARR, and customer health scoring. Analytical Rigor: Strong background in experimentation design, causal inference, and predictive modeling to inform customer-lifecycle strategy. Communication: Exceptional ability to translate data into compelling narratives for executives and cross-functional stakeholders. Business Impact: Demonstrated success improving onboarding efficiency, retention rates, or expansion revenue through data-driven initiatives.

At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Gilead's AI Research Center(ARC) is looking for a Principal Data Scientist to spearhead the adoption of AI/ML and transform our clinical development processes. This is a pivotal role where you will provide key thought leadership and drive our strategic vision for advanced analytics, with the goal of optimizing clinical trials, enhancing data-driven decision-making, and providing support for Real-World Evidence (RWE), Clinical Pharmacology, and Biomarkers initiatives. You will be a thought leader in applying AI/ML to real-world clinical challenges, taking deep involvement in all stages of technical development-from coding and configuring compute environments to model evaluation, review, and architecture design. You'll work closely with a variety of cross-functional teams, including architects, data engineers, and product managers, to scope, develop, and operationalize our AI-driven applications, with a specific focus on leveraging AI/ML to advance insights within RWE, Clinical Pharmacology, and Biomarkers. Responsibilities: Innovate and Strategize: Spearhead the strategic vision for leveraging AI/ML within clinical development. You'll partner with cross-functional leaders to identify high-impact opportunities and design innovative solutions that transform how we conduct trials and make data-driven decisions. Lead with Expertise: Guide the full lifecycle of machine learning models from initial concept to real-world application. This includes architecting scalable solutions, hands-on algorithm development, and ensuring models are rigorously evaluated and operationalized for use in RWE, Clinical Pharmacology, and Biomarkers. Mentor and Empower: Act as a force multiplier for our data science team. You'll coach and mentor senior and junior data scientists, fostering a culture of technical excellence and continuous learning. Translate and Execute: Serve as a bridge between technical teams and business stakeholders. You'll translate complex business challenges into precise data science problems and, in a product manager-like role, drive the development of these solutions from proof-of-concept to production. Drive Breakthroughs: Research and develop cutting-edge algorithms to solve critical challenges. This could involve using NLP for patient insights, computer vision for biomarker analysis, or predictive models to optimize trial logistics. You'll be at the forefront of applying these techniques in a biotech context. Build the Foundation: Design and implement the technical and process building blocks needed to scale our AI/ML capabilities. This includes working with IT partners to curate and operationalize the datasets essential for fueling our analytical pipelines. Influence and Advise: Interface directly with internal stakeholders, acting as a trusted advisor to help them understand the potential of advanced analytics and apply data-driven approaches to optimize clinical trial operations. Stay Ahead: Continuously monitor the landscape of machine learning and biopharmaceutical innovation. You'll ensure our team is leveraging the latest state-of-the-art techniques to maintain a competitive edge. Technical Skills: Advanced Model Development & Operationalization: Deep expertise in developing, deploying, and managing complex machine learning and deep learning algorithms at scale. This includes a profound understanding of model evaluation, scoring methodologies, and mitigation of model bias to ensure robust, ethical, and reliable outcomes. Data & Computational Proficiency: Fluent in Python or R and SQL, with hands-on experience in building and optimizing data pipelines for analytical and model development purposes. Cloud-Native AI/ML: Demonstrated experience with Cloud DevOps on AWS as it pertains to the entire data science lifecycle, from data ingestion to model serving and monitoring. Translational Research: Proven ability to translate foundational AI/ML research into functional, production-ready packages and applications that directly support strategic initiatives in areas like RWE, Clinical Pharmacology, and Biomarkers. Basic Qualifications: Doctorate and 5+ years of relevant experience OR Master's and 8+ years of relevant experience OR Bachelor's and 10+ years of relevant experience Preferred Qualifications: Ability to translate stakeholder needs into clear technical requirements, including those related to RWE, Clinical Pharmacology, and Biomarkers. Skill in scoping project requirements and developing timelines. Knowledge of product management principles. Experience with code management using Git. Strong technical documentation skills. Join us at the AI Research Center to shape the future of clinical development with groundbreaking AI/ML solutions, and contribute to advancements in RWE, Clinical Pharmacology, and Biomarkers! The salary range for this position is: Bay Area: $210,375.00 - $272,250.00.Other US Locations: $191,250.00 - $247,500.00. At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference. Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact. We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together. Job Description Gilead's AI Research Center(ARC) is looking for a Principal Data Scientist to spearhead the adoption of AI/ML and transform our clinical development processes. This is a pivotal role where you will provide key thought leadership and drive our strategic vision for advanced analytics, with the goal of optimizing clinical trials, enhancing data-driven decision-making, and providing support for Real-World Evidence (RWE), Clinical Pharmacology, and Biomarkers initiatives. You will be a thought leader in applying AI/ML to real-world clinical challenges, taking deep involvement in all stages of technical development-from coding and configuring compute environments to model evaluation, review, and architecture design. You'll work closely with a variety of cross-functional teams, including architects, data engineers, and product managers, to scope, develop, and operationalize our AI-driven applications, with a specific focus on leveraging AI/ML to advance insights within RWE, Clinical Pharmacology, and Biomarkers. Responsibilities: Innovate and Strategize: Spearhead the strategic vision for leveraging AI/ML within clinical development. You'll partner with cross-functional leaders to identify high-impact opportunities and design innovative solutions that transform how we conduct trials and make data-driven decisions. Lead with Expertise: Guide the full lifecycle of machine learning models from initial concept to real-world application. This includes architecting scalable solutions, hands-on algorithm development, and ensuring models are rigorously evaluated and operationalized for use in RWE, Clinical Pharmacology, and Biomarkers. Mentor and Empower: Act as a force multiplier for our data science team. You'll coach and mentor senior and junior data scientists, fostering a culture of technical excellence and continuous learning. Translate and Execute: Serve as a bridge between technical teams and business stakeholders. You'll translate complex business challenges into precise data science problems and, in a product manager-like role, drive the development of these solutions from proof-of-concept to production. Drive Breakthroughs: Research and develop cutting-edge algorithms to solve critical challenges. This could involve using NLP for patient insights, computer vision for biomarker analysis, or predictive models to optimize trial logistics. You'll be at the forefront of applying these techniques in a biotech context. Build the Foundation: Design and implement the technical and process building blocks needed to scale our AI/ML capabilities. This includes working with IT partners to curate and operationalize the datasets essential for fueling our analytical pipelines. Influence and Advise: Interface directly with internal stakeholders, acting as a trusted advisor to help them understand the potential of advanced analytics and apply data-driven approaches to optimize clinical trial operations. Stay Ahead: Continuously monitor the landscape of machine learning and biopharmaceutical innovation. You'll ensure our team is leveraging the latest state-of-the-art techniques to maintain a competitive edge. Technical Skills: Advanced Model Development & Operationalization: Deep expertise in developing, deploying, and managing complex machine learning and deep learning algorithms at scale. This includes a profound understanding of model evaluation, scoring methodologies, and mitigation of model bias to ensure robust, ethical, and reliable outcomes. Data & Computational Proficiency: Fluent in Python or R and SQL, with hands-on experience in building and optimizing data pipelines for analytical and model development purposes. Cloud-Native AI/ML: Demonstrated experience with Cloud DevOps on AWS as it pertains to the entire data science lifecycle, from data ingestion to model serving and monitoring. Translational Research: Proven ability to translate foundational AI/ML research into functional, production-ready packages and applications that directly support strategic initiatives in areas like RWE, Clinical Pharmacology, and Biomarkers. Basic Qualifications: Doctorate and 5+ years of relevant experience OR Master's and 8+ years of relevant experience OR Bachelor's and 10+ years of relevant experience Preferred Qualifications: Ability to translate stakeholder needs into clear technical requirements, including those related to RWE, Clinical Pharmacology, and Biomarkers. Skill in scoping project requirements and developing timelines. Knowledge of product management principles. Experience with code management using Git. Strong technical documentation skills. Join us at the AI Research Center to shape the future of clinical development with groundbreaking AI/ML solutions, and contribute to advancements in RWE, Clinical Pharmacology, and Biomarkers! The salary range for this position is: Bay Area: $210,375.00 - $272,250.00.Other US Locations: $191,250.00 - $247,500.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans*. For additional benefits information, visit: ****************************************************************** * Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans. For jobs in the United States: Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex , age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact ApplicantAccommodations@gilead.com for assistance. For more information about equal employment opportunity protections, please view the 'Know Your Rights' poster. NOTICE: EMPLOYEE POLYGRAPH PROTECTION ACT YOUR RIGHTS UNDER THE FAMILY AND MEDICAL LEAVE ACT PAY TRANSPARENCY NONDISCRIMINATION PROVISION Our environment respects individual differences and recognizes each employee as an integral member of our company. Our workforce reflects these values and celebrates the individuals who make up our growing team. Gilead provides a work environment free of harassment and prohibited conduct. We promote and support individual differences and diversity of thoughts and opinion. For Current Gilead Employees and Contractors: Please apply via the Internal Career Opportunities portal in Workday. Share: Job Requisition ID R0046852 Full Time/Part Time Full-Time Job Level Associate Director Click below to return to the Gilead Careers site Click below to see a list of upcoming events Click below to return to the Kite, a Gilead company Careers site #J-18808-Ljbffr

Data Scientist Everfit | Hybrid, San Francisco Bay Area Everfit is a fitness technology company building an AI-powered coaching platform that serves 280,000+ coaches and Millions of training clients globally. We're transforming how fitness professionals deliver personalized training and nutrition guidance to their clients through intelligent automation and data-driven insights. About the Role We're looking for a senior data scientist who is passionate about fitness and energized by turning data into actionable insights that help coaches and their clients succeed. You'll play a critical role in understanding user behavior, product performance, and business metrics to inform strategic decisions as we scale our platform. What You'll Do Product Analytics & User Insights Define and track key product metrics (activation, engagement, retention, churn) to measure product health and success. Conduct cohort, funnel, and retention analyses to uncover behavioral insights and inform feature prioritization. Identify opportunities to improve onboarding, engagement, and coach-client interactions. Experimentation & A/B Testing Own the experimentation framework and guide teams through hypothesis design, sample sizing, execution, and interpretation. Strategic Impact & Roadmapping Collaborate with leadership to translate data insights into roadmap priorities and measurable business outcomes. Build predictive models and scenario analyses to support forecasting, pricing, and product investment decisions. Establish best practices in data instrumentation, dashboarding, and self-serve analytics across teams. Technical Foundations Partner with data engineering to improve pipelines and instrumentation. Leverage tools such as SQL, Python/R, data visualization platforms, and experimentation platforms. Marketing Analytics & Optimization Analyze customer acquisition funnels and marketing performance to identify high-impact opportunities for growth and conversion. Partner with marketing and growth teams to design and evaluate campaign experiments What We're Looking For 4-6 years of experience in a data analyst or analytics role, preferably at a growth-stage tech company Strong proficiency in SQL and experience setting up data pipelines, transforming data, and analyzing large datasets Deep experience with creating dashboards and providing analysis on product analytics and data visualization tools (Amplitude, Looker, Tableau, Mode, or similar) Understanding of SaaS metrics and cohort analysis Experience with translating numerical findings into clear insights for non-technical team members Genuine passion for fitness, health, or wellness (we build for coaches so you need to understand their world) Bonus Points: Experience with Python or R for statistical analysis Experience in a PLG (Product-Led Growth) environment Experience working at a company during a hypergrowth phase Background in fitness, health, wellness, or coaching industries You'll thrive here if you: Are naturally curious and love asking "why" until you find the answer Are excited by fast-paced, high-growth environments with a passion for building out systems for scaling Enjoy collaborating with global teams and making complex topics understandable Are comfortable with ambiguity and can structure your own work Care deeply about the impact your insights have on real coaches and their clients Why Join Everfit Establish the foundations for Fitness Intelligence and help shape the future of coaching for millions around the world Work with autonomy and ownership on high-impact projects Join a collaborative, global team with experience from leading tech and fitness companies Enjoy competitive salary, equity, and performance bonuses Build something meaningful that helps people live better, healthier lives Everfit is an equal opportunity employer committed to building a diverse and inclusive team. We make employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected status. Ready to dive into data in the fitness intelligence space? We'd love to hear from you.

JOB TITLE: Staff Data Scientist DURATION: Full-time Pay Rate: $180,000 - $225,000 per year Must Haves: Strong foundation in Causal Inference, Statistical Analysis, and advanced Machine Learning methods Hands-on experience with a wide range of ML techniques, with a deep understanding of their advantages and limitations across different scenarios. Ability to integrate statistical expertise with machine learning methods to maximize the value and interpretability of ML solutions. Proficiency in Python, SQL, PyTorch, Spark/Ray, and stats/econometrics libraries. Experience deploying ML systems at scale on cloud platforms (GCP/Azure). Plusses: Publications and open-source contributions spanning the full spectrum of modern Machine Learning, from Statistical Learning (e.g., Bayesian modeling, causal inference, high-dimensional statistical methods) to Deep Learning (e.g., convolutional and transformer-based architectures) and Reinforcement Learning (e.g., dynamic programming, policy gradient methods). Exposure to ML observability: drift detection, retraining triggers, and causality-informed monitoring. Timeseries forecasting - will be working on it but can learn on the job Job Description: Chance to work on financial data for complex problems/challenges. Utilize LLMs/Genai systems and architectures to build and deploy state-of-the-art Genai systems. Our team collaborates closely with Finance teams to enhance financial planning and strategic decision-making through cutting-edge data-driven solutions. We specialize in a range of initiatives which provides actionable insights into trends and patterns and leveraging Generative AI (Genai) to produce concise, insightful summaries that empower decision-makers. By integrating these innovative approaches, we strive to drive efficiency, accuracy, and impactful outcomes in financial operations. Key Responsibilities: Lead the design, development, testing, and global deployment of large-scale time series forecasting models (including Regression models and state of the art time series specific models for example N-BEAST, PatchTST) to support complex retail and e-commerce hierarchies. Introduce causal modeling approaches to conduct impact analysis for future forecast. Continuously enhance forecasting strategies by incorporating advanced machine learning architectures, including RNNs (sequence modeling), CNNs (temporal feature extraction), and Attention-based mechanisms to improve accuracy, scalability, and robustness in time series forecasting. Advance causal modeling frameworks to quantify event impacts and integrate causal insights into forward-looking forecasts. Build and maintain experimentation pipelines (A/B testing, quasi-experiments, multi-armed bandits) for evaluating causal impacts of interventions. Mentor junior scientists, review research and production code, and ensure reproducibility and scalability in pipelines. Collaborate with engineering to implement forecasting + optimization systems in production (Airflow, Astronomer, Spark/Ray). Act as technical lead on multiple projects, balancing research rigor with business delivery.

Are you an experienced Data Scientist with a desire to excel? If so, then Talent Software Services may have the job for you! Our client is seeking an experienced Data Scientist to work at their company in Novato, CA. Client's Data Science is responsible for designing, capturing, analyzing, and presenting data that can drive key decisions for Clinical Development, Medical Affairs, and other business areas of Client. With a quality-by-design culture, Data Science builds quality data that is fit-for-purpose to support statistically sound investigation of critical scientific questions. The Data Science team develops solid analytics that are visually relevant and impactful in supporting key data-driven decisions across Client. The Data Management Science (DMS) group contributes to Data Science by providing complete, correct, and consistent analyzable data at data, data structure and documentation levels following international standards and GCP. The DMS Center of Risk Based Quality Management (RBQM) sub-function is responsible for the implementation of a comprehensive, cross-functional strategy to proactively manage quality risks for clinical trials. Starting at protocol development, the team collaborates to define critical-to-quality factors, design fit-for-purpose quality strategies, and enable ongoing oversight through centralized monitoring and data-driven risk management. The RBQM Data Scientist supports central monitoring and risk-based quality management (RBQM) for clinical trials. This role focuses on implementing and running pre-defined KRIs, QTLs, and other risk metrics using clinical data, with strong emphasis on SAS programming to deliver robust and scalable analytics across multiple studies. Primary Responsibilities/Accountabilities: The RBQM Data Scientist may perform a range of the following responsibilities, depending upon the study's complexity and the study's development stage: Implement and maintain pre-defined KRIs, QTLs, and triggers using robust SAS programs/macros across multiple clinical studies. Extract, transform, and integrate data from EDC systems (e.g., RAVE) and other clinical sources into analysis-ready SAS datasets. Run routine and ad-hoc RBQM/central monitoring outputs (tables, listings, data extracts, dashboard feeds) to support signal detection and study review. Perform QC and troubleshooting of SAS code; ensure outputs are accurate and efficient. Maintain clear technical documentation (specifications, validation records, change logs) for all RBQM programs and processes. Collaborate with Central Monitors, Central Statistical Monitors, Data Management, Biostatistics, and Study Operations to understand requirements and ensure correct implementation of RBQM metrics. Qualifications: PhD, MS, or BA/BS in statistics, biostatistics, computer science, data science, life science, or a related field. Relevant clinical development experience (programming, RBM/RBQM, Data Management), for example: PhD: 3+ years MS: 5+ years BA/BS: 8+ years Advanced SAS programming skills (hard requirement) in a clinical trials environment (Base SAS, Macro, SAS SQL; experience with large, complex clinical datasets). Hands-on experience working with clinical trial data.•Proficiency with Microsoft Word, Excel, and PowerPoint. Technical - Preferred / Strong Plus Experience with RAVE EDC. Awareness or working knowledge of CDISC, CDASH, SDTM standards. Exposure to R, Python, or JavaScript and/or clinical data visualization tools/platforms. Preferred: Knowledge of GCP, ICH, FDA guidance related to clinical trials and risk-based monitoring. Strong analytical and problem-solving skills; ability to interpret complex data and risk outputs. Effective communication and teamwork skills; comfortable collaborating with cross-functional, global teams. Ability to manage multiple programming tasks and deliver high-quality work in a fast-paced environment.

What you'll do... Join Client as a Principal Data Scientist to lead the development and deployment of advanced analytical models that drive strategic business decisions. This role requires expertise in machine learning, statistical analysis, and coding to design scalable solutions addressing complex business challenges. The position involves collaborating across functions to translate data insights into actionable strategies, mentoring team members, and ensuring high-quality data sourcing and validation. The ideal candidate will apply innovative techniques to enhance data-driven decision-making and contribute to Client's continued growth and operational excellence. About the team: The Data Science team employs advanced analytical and modeling techniques to address complex business challenges. They specialize in model assessment, validation, and deployment using tools such as Python, SQL, and machine learning frameworks. Collaborating closely with business stakeholders, the team translates requirements into actionable insights and data-driven solutions. Emphasizing rigorous statistical methods and data visualization, they ensure clear communication of findings. The team promotes continuous learning and innovation, guiding members in best practices and emerging technologies to deliver impactful results aligned with business goals. What you'll do: Develop and implement advanced machine learning models to address complex business challenges and drive data-informed decisions. Lead exploratory data analysis, feature engineering, and statistical modeling to extract actionable insights from data sources. Collaborate with cross-functional teams to translate business requirements into scalable data science solutions aligned with strategic objectives. Oversee model validation, tuning, deployment, and lifecycle management to ensure accuracy, robustness, and sustainability. Mentor and guide team members on analytical techniques, coding best practices, and data visualization to enhance overall team capability. Communicate findings effectively to stakeholders, supporting data-driven decision-making and continuous improvement initiatives. What you'll bring: Extensive experience in developing and deploying machine learning models using Python and related frameworks. Proficiency in advanced statistical analysis and data visualization techniques to derive actionable business insights. Strong knowledge of data sourcing, quality assessment, and management within complex business environments. Expertise in model validation, tuning, and lifecycle management to ensure robust and scalable solutions. Ability to translate business requirements into technical strategies and lead cross-functional teams effectively. Familiarity with cloud platforms such as AWS SageMaker for scalable model development and deployment. Demonstrated leadership in mentoring associates and driving continuous improvement in data science practices. Minimum Qualifications... Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications. Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 years' experience in an analytics or related field Preferred Qualifications... Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications. Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Client's accessibility standards and guidelines for supporting an inclusive culture. About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit ************************ US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Ensures effective and efficient operations through conducting operations analyses (i.e. operational effectiveness and capacity utilization), and recommends improvements. Details Job ID-26-00519

The Opportunity: As a data scientist, you're excited at the prospect of unlocking the secrets held by a data set, and you're fascinated by the possibilities presented by IoT, machine learning, and artificial intelligence. In an increasingly connected world, massive amounts of structured and unstructured data open new opportunities. As a data scientist at Booz Allen, you can help turn these complex data sets into useful information to solve global challenges. Across private and public sectors-from fraud detection to cancer research to national intelligence-we need you to help find the answers in the data. On our team, you'll use your data science expertise to help the client conduct training assessments and after actions based on data generated during live, virtual and constructive training. You'll work closely with clients to understand their questions and needs, and then dig into their data-rich environments to find the pieces of their information puzzle. You'll use the right combination of tools and frameworks to turn sets of disparate data points into objective answers to increase technical and tactical expertise of Marine Corps units. Ultimately, you'll provide a deep understanding of the data, what it all means, and how it can be used to improve Marine Corps training readiness. Work with us as we use data science for good. Join us. The world can't wait. You Have: 5+ years of experience with data exploration, data cleaning, data analysis, data visualization, or data mining 5+ years of experience with statistical and general-purpose programming languages for data analysis 5+ years of experience analyzing structured and unstructured data sources Experience developing predictive data models, quantitative analyses and visualization of targeted data sources Experience leading the development of solutions to complex programs Experience with natural language processing, text mining, or machine learning techniques Secret clearance Bachelor's degree Nice If You Have: Experience working with Marine Corps Live, Virtual and Constructive Training Systems Experience with distributed data and computing tools, including MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL Experience with visualization packages, including Plotly, Seaborn, or ggplot2 Clearance: Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; Secret clearance is required. Compensation At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs. Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page. Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen's total compensation package for employees. This posting will close within 90 days from the Posting Date. Identity Statement As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud. Work Model Our people-first culture prioritizes the benefits of flexibility and collaboration, whether that happens in person or remotely. If this position is listed as remote or hybrid, you'll periodically work from a Booz Allen or client site facility. If this position is listed as onsite, you'll work with colleagues and clients in person, as needed for the specific role. Commitment to Non-Discrimination All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.

Title: Operational Data Quality & Process Analyst Reporting to Director of Sales Operations | Supporting Sales Ops, Clinical Ops, AOEs, Finance & Training , preferably in the central time zone Overview HALO is scaling rapidly from 54 to 150+ active sites by March, and our operational success relies on accurate, reliable, and consistent site-level data. Today, much of our workflow is manual, spreadsheet-driven, and lacks standardized structure. We're hiring an Operational Data Quality & Process Analyst who will build structure where it doesn't exist, enforce data hygiene and accountability, and transform spreadsheet-based inputs into high-impact Tableau dashboards and executive-ready insights. This role is part analyst, part process architect, and part data quality guardian. You will be the bridge between manual PN data entry and the dashboards Sales Ops, Clinical Ops, and leadership rely on for decisions. If you enjoy creating order out of chaos, designing scalable workflows, and improving data reliability, this is the perfect role. Key Responsibilities Data Quality & Governance (Primary Focus) Own the daily/weekly data quality control of Patient Navigator (PN) trackers across 54+ sites (scaling to 150+). Implement structured QA processes, data validation rules, missing-data checks, and formatting standards. Identify discrepancies and recurring PN data issues; drive accountability across AOEs, PN leaders, and Clinical Ops. Create SOPs for data entry, quality checks, submission cadence, and version control. Tableau Dashboards Built from Spreadsheets (Highlighting this as a core responsibility) Build and maintain Tableau dashboards sourced directly from Excel/CSV spreadsheets-not databases. Clean, structure, normalize, and prepare manual spreadsheet data so it can flow seamlessly into Tableau. Manage extracts, refresh schedules, calculated fields, and metadata organization. Ensure dashboards consistently reflect accurate, timely, and complete site performance data. Troubleshoot dashboard breaks caused by inconsistent PN data and drive corrective actions. Operational Process Design Create scalable processes for data collection, QC, and reporting to support the expansion to 150+ sites. Standardize spreadsheet templates, naming conventions, definitions, and governance practices. Partner with Training to ensure PN teams understand data expectations and entry requirements. Design workflows that reduce messiness, improve compliance, and increase reliability of operational metrics. Site Launch Analytics Support Sales Ops and Clinical Ops with analytical views for new site and active site launch performance. Track early workflow indicators (form fills, tech handoff, outreach compliance, etc.). Develop quick-turn performance summaries to support launch readiness and site viability assessments. Cross-Functional Collaboration This role partners closely with: Sales Operations - site performance reporting, launch analytics Clinical Operations - workflow metrics, adoption trends Area Operations Executives (AOEs) - operational compliance, PN accountability Training - standardizing data entry habits Finance - profitability inputs & validation Patient Navigator Team - frontline documentation & data hygiene Executive Reporting & Presentation Support Create PowerPoint slides for Sales Ops, Clinical Ops, and leadership meetings. Translate dashboards and spreadsheet insights into clean, executive-ready visuals and summaries. Support narrative development for launch reviews, performance updates, and operational deep dives. Qualifications & Skills 2-5 years experience in data quality, operational analytics, or process-focused data roles (healthcare preferred). Advanced Excel expertise (XLOOKUP, pivots, structured tables, validation, conditional logic). Proficient in Tableau, with experience building dashboards from spreadsheet-based sources (Excel/CSV). Strong ability to normalize messy data, prepare inputs for BI tools, and troubleshoot refresh issues. Experience creating SOPs, process flows, and standardized data frameworks. Excellent PowerPoint skills (presentations, visuals, narratives). Strong communication skills with the ability to influence accountability across non-technical teams. Highly detail-oriented with a passion for accuracy and structure. Thrives in ambiguous, fast-paced environments. Nice to Have Experience with Tableau Prep. Exposure to SQL concepts (not required, future-friendly). Experience in patient operations, clinic workflows, or care coordination analytics. Why This Role Matters This analyst becomes the backbone of HALO's operational data. They ensure: dashboards work site workflows are measurable PN teams stay accountable leadership has accurate visibility launches run smoothly data chaos becomes data discipline This role directly impacts scalability, performance, and profitability as HALO continues rapid expansion. Salary: $75,000-$85,000/annually, based on experience

Gathers, analyzes, and interprets a wide variety of programmatic data. Designs and conducts data analysis. Prepares reports, charts, tables, and other visual aids to interpret and communicate data and results. Manages operations of several information systems and provides technical assistance to academic and administrative users statewide. This position is a career appointment that is 100% fixed. The home department is the Program Planning & Evaluation Department. While this position normally is based in Oakland, CA, this position is eligible for hybrid flexible work arrangements for applicants living in the State of California at this time. Please note that hybrid flexible work arrangements are subject to change by the University. Pay Scale: $88,900.00/year to $126,400.00/year Job Posting Close Date: This job is open until filled. The first application review date will be 10/24/2025. Key Responsibilities: 35% Gathers, analyzes, prepares, and summarizes the collection of information and data. Recommends approaches, trends, sources, and uses. Writes complex queries to gather programmatic data from multiple systems, using SQL in Microsoft SQL Server Management Studio and Microsoft Access, for annual reporting and ad hoc requests. Analyzes and prepares data to inform administrative and program decision making. Provides leadership to compile data for the Program Planning and Evaluation team and contributes to the analysis to meet annual federal program reporting requirements, strategic communications, and advocacy efforts. 20% Manages day-to-day operations for several information systems, including the following federal systems: The National Institute of Food Agriculture's (NIFA) Reporting System; the Research, Extension, and Education Project Online Reporting Tool; and the National Information Management and Support System, with over 500 UC ANR academic users. Provides training and technical assistance to users and to campus partners. Is a core member of the multicampus Program Reporting Group with administrative staff from the Deans' Offices. Liaises with Deans' Offices across multiple campuses and with USDA NIFA on policy and technical questions. Is a core member of the Product Owner Group for Project Board, the UC Cooperative Extension information system developed in-house, working closely with IT that is responsible for programming the system. Conducts testing when enhancements are deployed. Provides technical assistance to users statewide. Be a core team member, working with IT, to replace the publications data collection system Bibliography Project to improve administrative efficiencies. 20% Develops systems for organizing data to analyze, identify, and report trends. Structures and categorizes raw data to make it easily accessible, usable, and analyzable. Completes tasks such as data cleaning, standardization, classification, and potentially data warehousing. For example, retrieves, analyzes, and compiles UCPath data, the UC systemwide personnel system, for all UC ANR academics across multiple campuses and locations, to provide a quarterly report to leadership to illustrate trends and inform their academic staffing decisions. Manages an annual statewide survey of community educators to collect on data programmatic scope. Organizes and updates this academic and programmatic staff data in large, complex tables. 15% Prepares data for presentation in clear and compelling ways for a variety of audiences including administrators across the UC system and academics across disciplines, from senior leadership to researchers in the field, as well as UC ANR clientele/members of the public. For example, manages the programmatic and non-sensitive personnel data tasks for presentation in the online ArcGIS UC ANR Programmatic Footprint Maps. Tests maps to ensure the data is represented properly. Acts as a member of the project team that works on continued process improvements and map data enhancements. 5% Analyzes the interrelationships of data and defines logical aspects of data sets. Contributes to researching, assessing, and selecting new data reporting products. 5% Implements related business processes. Adapts processes to retrieve and analyze programmatic data when organization makes related changes. Manages proposal submission and provides process oversight for academic position planning and funding opportunities. Requirements: Bachelor's degree in related area and / or equivalent experience / training. Thorough skills in analysis and consultation. Skills to communicate complex information in a clear and concise manner both verbally and in writing. Skills in project management. Skills at a level to evaluate alternate solutions and develop recommendation. Ability to create and edit tables in Structured Query Language (SQL). Ability to work independently and with a team. Interpersonal and verbal skills to effectively communicate with diplomacy and to interact with a wide range of academics and staff. Special Conditions of Employment: Must possess valid California Driver's License to drive a County or University vehicle. Ability and means to travel on a flexible schedule as needed, proof of liability damage insurance on vehicle used is required. Reimbursement of job-related travel will be reimbursed according to University policies. The University reserves the right to make employment contingent upon successful completion of the background check. This is a designated position requiring a background check and may require fingerprinting due to the nature of the job responsibilities. UC ANR does hire people with conviction histories and reviews information received in the context of the job responsibilities. As of January 1, 2014, ANR is a smoke- and tobacco-free environment in which smoking, the use of smokeless tobacco products, and the use of unregulated nicotine products (e-cigarettes), is strictly prohibited. As a condition of employment, you will be required to comply with the University of California Policy on Vaccination Programs, as may be amended or revised from time to time. Federal, state, or local public health directives may impose additional requirements. Exercise the utmost discretion in managing sensitive information learned in the course of performing their duties. Sensitive information includes but is not limited to employee and student records, health and patient records, financial data, strategic plans, proprietary information, and any other sensitive or non-public information learned during the course and scope of employment. Understands that sensitive information should be shared on a limited basis and actively takes steps to limit access to sensitive information to individuals who have legitimate business need to know. Ensure that sensitive information is properly safeguarded. Follow all organizational policies and laws on data protection and privacy. This includes secure handling of physical and digital records and proper usage of IT systems to prevent data leaks. The unauthorized or improper disclosure of confidential work-related information obtained from any source on any work-related matter is a violation of these expectations. Misconduct Disclosure Requirement: As a condition of employment, the final candidate who accepts a conditional offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; received notice of any allegations or are currently the subject of any administrative or disciplinary proceedings involving misconduct; have left a position after receiving notice of allegations or while under investigation in an administrative or disciplinary proceeding involving misconduct; or have filed an appeal of a finding of misconduct with a previous employer. a. "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer. For reference, below are UC's policies addressing some forms of misconduct: https://apptrkr.com/get_redirect.php?id=6854006&target URL= Misconduct Disclosure Requirement: As a condition of employment, the final candidate who accepts a conditional offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; received notice of any allegations or are currently the subject of any administrative or disciplinary proceedings involving misconduct; have left a position after receiving notice of allegations or while under investigation in an administrative or disciplinary proceeding involving misconduct; or have filed an appeal of a finding of misconduct with a previous employer. a. "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer. For reference, below are UC's policies addressing some forms of misconduct: UC Sexual Violence and Sexual Harassment Policy UC Anti-Discrimination Policy Abusive Conduct in the Workplace To apply, please visit: https://careerspub.universityofcalifornia.edu/psc/ucanr/EMPLOYEE/HRMS/c/HRS_HRAM_FL.HRS_CG_SEARCH_FL.GBL?Page=HRS_APP_JBPST_FL&JobOpeningId=81754&PostingSeq=1&SiteId=17&language Cd=ENG&FOCUS=Applicant Copyright ©2025 Jobelephant.com Inc. All rights reserved. Posted by the FREE value-added recruitment advertising agency jeid-818690a67388c64daf0229add8bd4337

Salary: $200-250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We're looking for a Staff Data Scientist to drive Sales and Go-to-Market (GTM) analytics, applying advanced modeling and experimentation to accelerate revenue growth and optimize the full sales funnel. About the Role As the senior data scientist supporting Sales and GTM, you will combine statistical modeling, experimentation, and advanced analytics to inform strategy and guide decision-making across our revenue organization. Your work will help leadership understand pipeline health, predict outcomes, and identify the levers that unlock sustainable growth. Key Responsibilities Model the Business: Build forecasting and propensity models for pipeline generation, conversion rates, and revenue projections. Optimize the Sales Funnel: Analyze lead scoring, opportunity progression, and deal velocity to recommend improvements in acquisition, qualification, and close rates. Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of pricing, incentives, and campaign initiatives. Advanced Analytics for GTM: Apply machine learning and statistical techniques to segment accounts, predict churn/expansion, and identify high-value prospects. Cross-Functional Partnership: Work closely with Sales, Marketing, RevOps, and Product to influence GTM strategy and ensure data-driven decisions. Data Infrastructure Collaboration: Partner with Analytics Engineering to define data requirements, ensure data quality, and enable self-serve reporting. Strategic Insights: Present findings to executive leadership, translating complex analyses into actionable recommendations. About You Experience: 6+ years in data science or advanced analytics roles, with significant time spent in B2B SaaS or developer tools environments. Technical Depth: Expert in SQL and proficient in Python or R for statistical modeling, forecasting, and machine learning. Domain Knowledge: Strong understanding of sales analytics, revenue operations, and product-led growth (PLG) motions. Analytical Rigor: Skilled in experimentation design, causal inference, and building predictive models that influence GTM strategy. Communication: Exceptional ability to tell a clear story with data and influence senior stakeholders across technical and business teams. Business Impact: Proven record of driving measurable improvements in pipeline efficiency, conversion rates, or revenue outcomes.

Data Scientist Everfit | Hybrid, San Francisco Bay Area Everfit is a fitness technology company building an AI-powered coaching platform that serves 280,000+ coaches and Millions of training clients globally. We're transforming how fitness professionals deliver personalized training and nutrition guidance to their clients through intelligent automation and data-driven insights. About the Role We're looking for a senior data scientist who is passionate about fitness and energized by turning data into actionable insights that help coaches and their clients succeed. You'll play a critical role in understanding user behavior, product performance, and business metrics to inform strategic decisions as we scale our platform. What You'll Do Product Analytics & User Insights Define and track key product metrics (activation, engagement, retention, churn) to measure product health and success. Conduct cohort, funnel, and retention analyses to uncover behavioral insights and inform feature prioritization. Identify opportunities to improve onboarding, engagement, and coach-client interactions. Experimentation & A/B Testing Own the experimentation framework and guide teams through hypothesis design, sample sizing, execution, and interpretation. Strategic Impact & Roadmapping Collaborate with leadership to translate data insights into roadmap priorities and measurable business outcomes. Build predictive models and scenario analyses to support forecasting, pricing, and product investment decisions. Establish best practices in data instrumentation, dashboarding, and self-serve analytics across teams. Technical Foundations Partner with data engineering to improve pipelines and instrumentation. Leverage tools such as SQL, Python/R, data visualization platforms, and experimentation platforms. Marketing Analytics & Optimization Analyze customer acquisition funnels and marketing performance to identify high-impact opportunities for growth and conversion. Partner with marketing and growth teams to design and evaluate campaign experiments What We're Looking For 4-6 years of experience in a data analyst or analytics role, preferably at a growth-stage tech company Strong proficiency in SQL and experience setting up data pipelines, transforming data, and analyzing large datasets Deep experience with creating dashboards and providing analysis on product analytics and data visualization tools (Amplitude, Looker, Tableau, Mode, or similar) Understanding of SaaS metrics and cohort analysis Experience with translating numerical findings into clear insights for non-technical team members Genuine passion for fitness, health, or wellness (we build for coaches so you need to understand their world) Bonus Points: Experience with Python or R for statistical analysis Experience in a PLG (Product-Led Growth) environment Experience working at a company during a hypergrowth phase Background in fitness, health, wellness, or coaching industries You'll thrive here if you: Are naturally curious and love asking "why" until you find the answer Are excited by fast-paced, high-growth environments with a passion for building out systems for scaling Enjoy collaborating with global teams and making complex topics understandable Are comfortable with ambiguity and can structure your own work Care deeply about the impact your insights have on real coaches and their clients Why Join Everfit Establish the foundations for Fitness Intelligence and help shape the future of coaching for millions around the world Work with autonomy and ownership on high-impact projects Join a collaborative, global team with experience from leading tech and fitness companies Enjoy competitive salary, equity, and performance bonuses Build something meaningful that helps people live better, healthier lives Everfit is an equal opportunity employer committed to building a diverse and inclusive team. We make employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected status. Ready to dive into data in the fitness intelligence space? We'd love to hear from you.

Chance to work on financial data for complex problems/challenges. Utilize LLMs/Genai systems and architectures to build and deploy state-of-the-art Genai systems. Our team collaborates closely with Finance teams to enhance financial planning and strategic decision-making through cutting-edge data-driven solutions. We specialize in a range of initiatives which provides actionable insights into trends and patterns and leveraging Generative AI (Genai) to produce concise, insightful summaries that empower decision-makers. By integrating these innovative approaches, we strive to drive efficiency, accuracy, and impactful outcomes in financial operations. About Team: Our team works closely with our US stores and eCommerce business to better serve customers by empowering team members, stores, and merchants with technological innovation. From groceries and entertainment to sporting goods and crafts, extensive selection that our customers value, whether they shop online through one of our mobile apps, or in-store. Focus areas include customers, stores and employees, in-store service, merchant tools, merchant data science, and search and personalization. What you'll do Lead the design, development, testing, and global deployment of large-scale time series forecasting models (including Regression models and state of the art time series specific models for example N-BEAST, PatchTST) to support complex retail and e-commerce hierarchies. Introduce causal modeling approaches to conduct impact analysis for future forecast. Continuously enhance forecasting strategies by incorporating advanced machine learning architectures, including RNNs (sequence modeling), CNNs (temporal feature extraction), and Attention-based mechanisms to improve accuracy, scalability, and robustness in time series forecasting. Advance causal modeling frameworks to quantify event impacts and integrate causal insights into forward-looking forecasts. Build and maintain experimentation pipelines (A/B testing, quasi-experiments, multi-armed bandits) for evaluating causal impacts of interventions. Mentor junior scientists, review research and production code, and ensure reproducibility and scalability in pipelines. Collaborate with engineering to implement forecasting + optimization systems in production (Airflow, Astronomer, Spark/Ray). Act as technical lead on multiple projects, balancing research rigor with business delivery. What you'll bring Strong foundation in Time Series Forecasting, Causal Inference, Statistical Analysis, and advanced Machine Learning methods Hands-on experience with a wide range of ML techniques, with a deep understanding of their advantages and limitations across different scenarios. Ability to integrate statistical expertise with machine learning methods to maximize the value and interpretability of ML solutions. Proficiency in Python, SQL, PyTorch, Spark/Ray, and stats/econometrics libraries. Experience deploying ML systems at scale on cloud platforms (GCP/Azure). Great to have Publications and open-source contributions spanning the full spectrum of modern Machine Learning, from Statistical Learning (e.g., Bayesian modeling, causal inference, high-dimensional statistical methods) to Deep Learning (e.g., convolutional and transformer-based architectures) and Reinforcement Learning (e.g., dynamic programming, policy gradient methods). Exposure to ML observability: drift detection, retraining triggers, and causality-informed monitoring. Background in retail, e-commerce, or operations analytics. About US Tech Solutions: US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit ************************ US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Recruiter Details: Recruiter name: Ajeet Kumar Recruiter's email id : ***************************** JobDiva ID :: JobDiva # 25-53396

Salary: $200-250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We're expanding our data science organization to accelerate customer success after the initial sale-driving onboarding, retention, expansion, and long-term revenue growth. About the Role As the senior data scientist supporting post-sales teams, you will use advanced analytics, experimentation, and predictive modeling to guide strategy across Customer Success, Account Management, and Renewals. Your insights will help leadership forecast expansion, reduce churn, and identify the levers that unlock sustainable net revenue retention. Key Responsibilities Forecast & Model Growth: Build predictive models for renewal likelihood, expansion potential, churn risk, and customer health scoring. Optimize the Customer Journey: Analyze onboarding flows, product adoption patterns, and usage signals to improve activation, engagement, and time-to-value. Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of onboarding programs, success initiatives, and pricing changes on retention and expansion. Revenue Insights: Partner with Customer Success and Sales to identify high-value accounts, cross-sell opportunities, and early warning signs of churn. Cross-Functional Partnership: Collaborate with Product, RevOps, Finance, and Marketing to align post-sales strategies with company growth goals. Data Infrastructure Collaboration: Work with Analytics Engineering to define data requirements, maintain data quality, and enable self-serve dashboards for Success and Finance teams. Executive Storytelling: Present clear, actionable recommendations to senior leadership that translate complex analysis into strategic decisions. About You Experience: 6+ years in data science or advanced analytics, with a focus on post-sales, customer success, or retention analytics in a B2B SaaS environment. Technical Skills: Expert SQL and proficiency in Python or R for statistical modeling, forecasting, and machine learning. Domain Knowledge: Deep understanding of SaaS metrics such as net revenue retention (NRR), gross churn, expansion ARR, and customer health scoring. Analytical Rigor: Strong background in experimentation design, causal inference, and predictive modeling to inform customer-lifecycle strategy. Communication: Exceptional ability to translate data into compelling narratives for executives and cross-functional stakeholders. Business Impact: Demonstrated success improving onboarding efficiency, retention rates, or expansion revenue through data-driven initiatives.

Data Scientist Everfit | Hybrid, San Francisco Bay Area Everfit is a fitness technology company building an AI-powered coaching platform that serves 280,000+ coaches and Millions of training clients globally. We're transforming how fitness professionals deliver personalized training and nutrition guidance to their clients through intelligent automation and data-driven insights. About the Role We're looking for a senior data scientist who is passionate about fitness and energized by turning data into actionable insights that help coaches and their clients succeed. You'll play a critical role in understanding user behavior, product performance, and business metrics to inform strategic decisions as we scale our platform. What You'll Do Product Analytics & User Insights Define and track key product metrics (activation, engagement, retention, churn) to measure product health and success. Conduct cohort, funnel, and retention analyses to uncover behavioral insights and inform feature prioritization. Identify opportunities to improve onboarding, engagement, and coach-client interactions. Experimentation & A/B Testing Own the experimentation framework and guide teams through hypothesis design, sample sizing, execution, and interpretation. Strategic Impact & Roadmapping Collaborate with leadership to translate data insights into roadmap priorities and measurable business outcomes. Build predictive models and scenario analyses to support forecasting, pricing, and product investment decisions. Establish best practices in data instrumentation, dashboarding, and self-serve analytics across teams. Technical Foundations Partner with data engineering to improve pipelines and instrumentation. Leverage tools such as SQL, Python/R, data visualization platforms, and experimentation platforms. Marketing Analytics & Optimization Analyze customer acquisition funnels and marketing performance to identify high-impact opportunities for growth and conversion. Partner with marketing and growth teams to design and evaluate campaign experiments What We're Looking For 4-6 years of experience in a data analyst or analytics role, preferably at a growth-stage tech company Strong proficiency in SQL and experience setting up data pipelines, transforming data, and analyzing large datasets Deep experience with creating dashboards and providing analysis on product analytics and data visualization tools (Amplitude, Looker, Tableau, Mode, or similar) Understanding of SaaS metrics and cohort analysis Experience with translating numerical findings into clear insights for non-technical team members Genuine passion for fitness, health, or wellness (we build for coaches so you need to understand their world) Bonus Points: Experience with Python or R for statistical analysis Experience in a PLG (Product-Led Growth) environment Experience working at a company during a hypergrowth phase Background in fitness, health, wellness, or coaching industries You'll thrive here if you: Are naturally curious and love asking "why" until you find the answer Are excited by fast-paced, high-growth environments with a passion for building out systems for scaling Enjoy collaborating with global teams and making complex topics understandable Are comfortable with ambiguity and can structure your own work Care deeply about the impact your insights have on real coaches and their clients Why Join Everfit Establish the foundations for Fitness Intelligence and help shape the future of coaching for millions around the world Work with autonomy and ownership on high-impact projects Join a collaborative, global team with experience from leading tech and fitness companies Enjoy competitive salary, equity, and performance bonuses Build something meaningful that helps people live better, healthier lives Everfit is an equal opportunity employer committed to building a diverse and inclusive team. We make employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability, or any other protected status. Ready to dive into data in the fitness intelligence space? We'd love to hear from you.

Salary: $200-250k base + RSUs This fast-growing Series E AI SaaS company is redefining how modern engineering teams build and deploy applications. We're looking for a Staff Data Scientist to drive Sales and Go-to-Market (GTM) analytics, applying advanced modeling and experimentation to accelerate revenue growth and optimize the full sales funnel. About the Role As the senior data scientist supporting Sales and GTM, you will combine statistical modeling, experimentation, and advanced analytics to inform strategy and guide decision-making across our revenue organization. Your work will help leadership understand pipeline health, predict outcomes, and identify the levers that unlock sustainable growth. Key Responsibilities Model the Business: Build forecasting and propensity models for pipeline generation, conversion rates, and revenue projections. Optimize the Sales Funnel: Analyze lead scoring, opportunity progression, and deal velocity to recommend improvements in acquisition, qualification, and close rates. Experimentation & Causal Analysis: Design and evaluate experiments (A/B tests, uplift modeling) to measure the impact of pricing, incentives, and campaign initiatives. Advanced Analytics for GTM: Apply machine learning and statistical techniques to segment accounts, predict churn/expansion, and identify high-value prospects. Cross-Functional Partnership: Work closely with Sales, Marketing, RevOps, and Product to influence GTM strategy and ensure data-driven decisions. Data Infrastructure Collaboration: Partner with Analytics Engineering to define data requirements, ensure data quality, and enable self-serve reporting. Strategic Insights: Present findings to executive leadership, translating complex analyses into actionable recommendations. About You Experience: 6+ years in data science or advanced analytics roles, with significant time spent in B2B SaaS or developer tools environments. Technical Depth: Expert in SQL and proficient in Python or R for statistical modeling, forecasting, and machine learning. Domain Knowledge: Strong understanding of sales analytics, revenue operations, and product-led growth (PLG) motions. Analytical Rigor: Skilled in experimentation design, causal inference, and building predictive models that influence GTM strategy. Communication: Exceptional ability to tell a clear story with data and influence senior stakeholders across technical and business teams. Business Impact: Proven record of driving measurable improvements in pipeline efficiency, conversion rates, or revenue outcomes.