Data scientist jobs in Salinas, CA - 368 jobs

Everfit | Hybrid, San Francisco Bay Area Everfit is a fitness technology company building an AI-powered coaching platform that serves 280,000+ coaches 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 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 Analyze user engagement patterns, retention metrics, and feature adoption to identify opportunities for product improvement Build dashboards and reports that make complex data accessible to cross-functional teams Partner with Product, Engineering, and Marketing to design experiments and measure their impact Dive deep into the coaching journey to understand what drives client outcomes and coach success Translate data findings into clear narratives and recommendations for leadership Support the development of our AI/ML capabilities by identifying data patterns and opportunities What We're Looking For Non-negotiable: Genuine passion for fitness, health, or wellness (we build for coaches so you need to understand their world) Strong proficiency in SQL and experience working with large datasets Experience with data visualization tools (Looker, Tableau, Mode, or similar) Ability to translate technical findings into insights for non-technical stakeholders Strongly preferred: 2-4 years of experience in a data analyst or analytics role, preferably at a growth-stage tech company Experience with Python or R for statistical analysis Familiarity with product analytics tools (Amplitude, Mixpanel, or similar) Understanding of SaaS metrics and cohort analysis Experience in a PLG (Product-Led Growth) environment Background in the fitness, health, or coaching industry You'll thrive here if you: Are naturally curious and love asking "why" until you find the answer Can balance rigor with speed-knowing when to dig deeper and when to move forward Enjoy collaborating with diverse 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 What We Offer Competitive compensation with equity Flexible PTO and remote-first culture The opportunity to directly impact the success of 280,000+ coaches worldwide Our Team We're a distributed team of ~15 in the US, scaling to 2 - 3x that by end of 2026. We value depth over superficial growth, shipping over endless planning, and genuine fitness passion over resume credentials.

The WCIRB is looking for an experienced Lead Actuarial Analyst interested in having a critical role in the WCIRB's actuarial functions. This position will be directly involved in the WCIRB's core ratemaking and data analysis functions with opportunities for growth, independence, and external communication. The Workers' Compensation Insurance Rating Bureau of California (WCIRB) is California's trusted, objective provider of actuarially-based information and research, advisory pure premium rates, and educational services integral to a healthy workers' compensation system. The WCIRB is a California unincorporated, private, nonprofit association comprised of all companies licensed to transact workers' compensation insurance in California, and has over 400 member companies. No state money is used to fund its operations. The operations of the WCIRB are funded primarily by membership fees and assessments. To accurately measure the cost of providing workers' compensation benefits, the WCIRB performs a number of functions, including collection of premium and loss data on every workers' compensation insurance policy, examination of policy documents, inspections of insured businesses, and test audits of insurer payroll audits and claims classification. The WCIRB employs approximately 175 people. The home office is located in San Francisco, California. Summary of Position The Lead Actuarial Analyst is responsible for (1) leading various complex actuarial analyses and core projects, (2) supervising and maintaining data collection processes, and (3) providing input and insight regarding trends, cost drivers, and other key components of the WCIRB's core ratemaking functions. The Lead Actuarial Analyst works independently and collaboratively with other members of the Actuarial Services team, other WCIRB research teams and other WCIRB departments, with little to no supervision, and where work is peer reviewed by other analysts or leaders. The Lead Actuarial Analyst reports to the Vice President, Actuary. Essential Duties and Responsibilities Leads the analysis and evaluation of statistical data pertaining to pure premium rates; identifies trends or cost drivers; prepares materials for committees or rate filings to evaluate impact of various cost drivers on pure premium rates. Leads actuarial analyses of aggregate data and ratemaking methodologies; recommends adjustments to actuarial ratemaking methodologies to the Vice President, Actuary and Chief Actuary; periodically validates appropriateness of methodologies. Provides key deliverables and correspondence with WCIRB members and other customers, such as the insurance department and governmental agencies, on complex data and other technical issues, with minimal or no supervision. Represents Actuarial department and provides subject matter expertise on actuarial data and data collection processes to representatives of other units of the WCIRB on various cross-functional projects and issues. Prepares, reviews, and analyzes various studies of aggregate and classification experience for rate filings and other reports produced by Actuarial Services included those presented to WCIRB Committees and Working Groups. Leads the Actuarial team's efforts in collaboration with the IT department on the development and changes to applications used by the Actuarial team and customers to submit, retrieve, and/or analyze data. Supervises the development and maintenance of data products and oversees the fulfillment of data requirements pursuant to statutory and regulatory mandates. Performs peer reviews of analysts' work. Supervises actuarial analysts in various aspects of analyses; oversees progress of projects and guides projects to completion in an accurate and timely manner. Education, Experience, and Skill Qualifications: Educational background (Bachelor's degree or above) in a technical field such as mathematics, actuarial science, applied statistics, or economics. Five years of experience as an actuarial analyst in a property/casualty insurance company, rating organization, consulting firm, or a state insurance department. Very strong professional communication skills, both verbally and in writing. Strong listening and interpersonal skills. A high level of ability in the utilization of mathematical techniques for the analysis of statistical information. The ability to develop a complete theoretical framework with precisely-defined relationships, as necessary in special studies or rate revisions. Very strong proficiency in the following three areas with six years' experience preferred: mathematics, applied statistics, and programming (in a language such as VBA, SQL, R, or Python). Proficiency in Microsoft Office Suite. Associate of the Casualty Actuarial Society (CAS) or at least six CAS exams with extensive related experience. Perks & Benefits Our employees enjoy a state of the art, energy-efficient, open work environment that nurtures collaboration and creativity. At the WCIRB, we go the extra mile to keep our employees happy and healthy. Proud to be recognized as a Plan Sponsor of the Year finalist for our commitment to retirement readiness through strong 401k and pension offerings. Some of our perks include: Hybrid work environment (40% onsite 60% remote) Medical, dental and vision benefits Competitive PTO Program 401K and pension plan Annual incentive plan Social activities Community volunteer involvement WCIRB is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. The successful candidate will reside in California and will work from our headquarters in San Francisco at least 40% of the time. We are NOT able to pay for relocation costs for candidates or to sponsor or take over sponsorship of an employment Visa at this time. Thank you for your interest in the WCIRB!

TikTok-Data Science team is responsible for all data science and analytics related work, cooperating with all key value chains in TikTok, including User Growth, PGC, Content Ecosystem, Social, Creation, Product Infrastructure, Research and Science etc. The goal of the team is to generate actionable insights from data and help the stakeholders to make the right decisions. Our main tasks include metrics defining, root cause analysis, experimentation methodology, feature/strategy evaluation and exploratory analysis to find more opportunities. The primary role of a Data Scientist for our Data team is to conduct deep analysis into user behavior, product features and content ecosystem to generate business insights that could be applied to actionable improving initiatives. You will work closely with cross-function teams, such as Product Management, Research and Development, Machine Learning Engineering, to improve user experience and fulfill growth of TikTok in all different regions. About Team Our social team's mission is to help people discover, build, and sustain meaningful connections. We design features that spark interactions, measure the health of relationships on our platform, and use experimentation and causal inference to ensure we're improving outcomes that matter-quality conversations, trusted interactions, and highly retained relationships. You'll collaborate closely with Product, Engineering, and Trust & Safety to turn insights into experiences that make connecting easier and better. What You'll Do * Experimentation & Causal Inference * Design, launch, and analyze A/B tests and quasi-experiments. * Ensure rigor: power analysis, guardrails, heterogeneity, and causal validity. * Social Graph & Connections * Analyze and model the social graph to understand how users connect. * Develop signals and strategies that drive high‑quality interactions and growth. * Metrics & Product Health * Define and monitor core product metrics and leading indicators. * Investigate metric movements and recommend data‑driven actions. * Insights to Action * Partner with Product and Engineering to turn findings into roadmap and features. * Communicate clearly with concise narratives and visualizations.Minimum Qualifications * Master's in a quantitative field with 2+ years of experience. * Proficiency in SQL and Python/R. * Strong statistical rigor and causal reasoning. Preferred Qualifications * PhD (2+ yrs) or MS (4+ yrs) industry experience. * Experience with: * Graph analysis, recommendations/ranking, and large‑scale experimentation. * Causal inference methods (e.g., diff‑in‑diff, matching, uplift). * Track record of product impact and effective cross‑functional collaboration. * Passion for social products and understanding human connection.

About ByteDance Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content. Why Join Us Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day. As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us. About the Team Our team plays a crucial role in ensuring the company's success. We seek people who are willing to learn and put in the effort to solve problems. Our challenges are not your regular day-to-day problems - you'll be part of a team that's developing new solutions to new challenges. It's working fast, at scale, and we're making a difference. We are looking for talents to join us on this exciting journey! Responsibilities Own and conduct data analysis related to live streaming and real-time communication (RTC) products. Ensure data quality by monitoring event tracking quality, participating in event tracking design reviews, and collaborating with the data engineering team. Build efficient data ETL processes and maintain data SLAs. Develop and maintain a comprehensive live streaming and RTC-related metrics system, including defining indicators, building dashboards, ensuring stability and availability, and conducting root cause analysis for metrics. Perform data analysis based on business requirements, support data analysis for special projects, and provide ongoing data analysis support. Support A/B testing initiatives by optimizing A/B testing processes, producing Libra indicators, providing attribution analysis, and generating A/B testing conclusions and reports. Drive business growth by identifying data optimization opportunities, providing optimization suggestions, and delivering tangible benefits. Develop and refine optimization methodologies over time. Collaborate with cross-functional teams, such as Product Management, Research and Development, and Technical Support, to identify and resolve online issues. Qualifications Must have a Master's degree or foreign equivalent degree in Computer Science, Engineering (any), Information Technology, Machine Learning, Statistics (any), Analytics, Data Science, Mathematics, or a related field, and 2 years of related work experience; OR a Bachelor's degree or foreign equivalent degree in Computer Science, Engineering (any), Information Technology, Machine Learning, Statistics (any), Analytics, Data Science, Mathematics, or a related field, and 5 years of post-bachelor's, progressive related work experience. Of the required experience, must have 2 years of experience in each of the following: Mining, preparing, cleansing, and analyzing structured data using statistical computing languages SQL, Python, and/or R for metrics creation, root cause analysis, and model preprocessing; Using SQL queries and data visualization tools to gather, process, visualize, and analyze large quantities of data to detect trends and anomalies in support of business opportunity identification; Analyzing large quantities of data to detect anomalies using Python and statistical analysis techniques; Developing and maintaining tables, views, indexes, datasets, and/or data pipelines to extract, clean, transform, load and maintain data across multiple databases; and Providing data-driven insights and recommendations to mitigate insufficiencies models based on model performance, regulations, or business requirements. Travel Requirement: International travel required up to 10%. Type: Full time, 40 hours/week Location: San Jose, CA Salary Range: $275850 - $395280 per year To Apply, click the apply button below. Contact *********************** if you have difficulty submitting resume through the website. ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. ByteDance is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at ****************************** #IND-DNI

The Health Sensing team builds outstanding technologies to support our users in living their healthiest, the happiest lives by providing them with objective, accurate, and timely information about their health and well-being. As part of the larger Sensor SW u0026 Prototyping team, we take a multimodal approach using a variety of data types across HW platforms, such as camera, PPG, and natural languages, to build products to support our users in living their healthiest, happiest lives. In this role, you will be at the forefront of developing and validating evaluation methodologies for Generative AI systems in health and wellbeing applications. You will design comprehensive human annotation frameworks, build automated evaluation tools, and conduct rigorous statistical analyses to ensure the reliability of both human and AI-based assessment systems. Your work will directly impact the quality and trustworthiness of customer-facing health products. In this role you will: - Design and analyze human evaluations of AI systems to create reliable annotation frameworks, and ensure validity and reliability of measurements of latent constructs - Develop and refine benchmarks and evaluation protocols, using statistical modeling, test theory, and task design to capture model performance across diverse contexts and user needs - Conduct statistical analysis of evaluation data to extract meaningful insights, identify systematic issues, and inform improvements to both models and evaluation processes - Analyze model behavior, identify weaknesses, and drive design decisions with failure analysis. Examples include, but not limited to: model experimentation, adversarial testing, counterfactual analysis, creating tools to assess model behavior and user impact - Collaborate with engineers to translate evaluation methods and analysis techniques into scalable, adaptable, and reliable solutions that can be reused across different features, use cases, and evaluation workflows - Work cross-functionally to apply methods to real-world applications with designers, clinical experts, and engineering teams across Hardware and Software - Independently run and analyze experiments for real improvements MS or PhD or equivalent experience in relevant fields Real-world experience with LLM-based evaluation systems and human annotation and human evaluation methodologies Experience in rigorous, evidence-based approaches to test development, e.g. quantitative and qualitative test design, reliability and validity analysis Customer-focused mindset with experience or strong interest in building consumer digital health and wellness products Strong communication skills and ability to work cross-functionally with technical and non-technical stakeholders BS and a minimum of 10 years relevant industry experience in a empirical field with emphasis on quantitative methodologies of human behavior, including HCI, Psychometrics, Quantitative or Experimental Psychology, Educational Measurement, Language Assessment, or a relevant field Proficiency in Python and ability to write clean, performant code and collaborate using standard software development practices (e.g. Git) Strong statistical analysis skills and experience in crafting experiments, validating data quality and model performance Experience in building and extending data and inference pipelines to process large scale datasets

The Company PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do - and they push us to ensure we take care of ourselves, each other, and our communities. Job Summary: This job will design and implement advanced data science models to support business needs. You will work with stakeholders to understand requirements and deliver solutions. Your role involves driving best practices in data science, ensuring data quality, and mentoring junior scientists. Job Description: Essential Responsibilities: * Lead and manage data science projects, ensuring timely delivery and alignment with business goals. * Develop and maintain data models, algorithms, and reporting systems to support data analysis and decision-making. * Analyze complex datasets to identify trends, patterns, and insights that drive strategic initiatives. * Collaborate with cross-functional teams to understand data needs and provide actionable insights. * Ensure data quality and integrity through regular audits and validation processes. * Mentor and guide junior data scientists, fostering a culture of continuous learning and improvement. Expected Qualifications: * 5+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. Additional Responsibilities & Preferred Qualifications: Advanced degree in a quantitative field (e.g., Data Science, Computer Science, Engineering, Statistics, Mathematics, Economics) with a strong analytical and problem-solving mindset. 7+ years of experience in Product Data Science, including A/B testing, experimentation, advanced analytics, and applied machine learning. Demonstrated success partnering with Product teams in domains such as Payments, eCommerce, or SaaS to shape strategy, inform roadmaps, and deliver impactful, data-driven insights. Proven ability to lead and manage data science and analytics projects end-to-end, from ideation to delivery, leveraging data modeling, machine learning algorithms, and advanced analytics techniques. Extensive experience analyzing high-volume, high-dimensional real-world data, focusing on scalable solutions and measurable business outcomes. Advanced proficiency in SQL and Python, with expertise in extracting, processing, and generating actionable insights from large, complex datasets. Hands-on experience with modern data tools and platforms, including Jupyter Notebooks, BigQuery, Teradata, Hadoop, and Hive. Expert in designing and building executive dashboards and impactful data visualizations using Tableau, Power BI, and Looker to drive data-informed decision-making at the leadership level. Exceptional communication and data storytelling skills, adept at translating complex analyses for both technical and non-technical audiences and influencing cross-functional decisions. Highly motivated, self-directed, and passionate about experimentation, product thinking, and navigating ambiguity while managing multiple projects in a fast-paced, results-driven environment Subsidiary: PayPal Travel Percent: 0 * The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is: Primary Location | Pay Range: San Jose, California | ($176,500.00 - $262,350.00 Annually) Additional Location(s) | Pay Range: No other locations are assigned to this requisition currently. Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable. This role is also eligible for a range of benefits which may include, medical, dental, vision, life and disability insurance, parental and family leave, 401(k) savings plan, paid time off, and other benefits. For more information visit ******************************* PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. Any such request is a red flag and likely part of a scam. To learn more about how to identify and avoid recruitment fraud please visit ************************************ For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations. Our Benefits: At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you. We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit ******************************* Who We Are: Click Here to learn more about our culture and community. Commitment to Diversity and Inclusion PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at ****************************************. Belonging at PayPal: Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal. Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.

Fullpower -AI delivers a complete B2B IoT platform for AI-powered algorithms, remote contactless biosensing together with end-to-end engineering services, and customization of software in the field of life sciences, health, and biotechnology. Fullpower's platform is vetted and deployed as a PaaS, backed by a patent portfolio of 135+ patents. Fullpower's key areas of expertise include contactless biosensing, remote monitoring, non-invasive sleep technology, and the development of new technologies for others in the life sciences and biotechnology fields. Fullpower's B2B PaaS customers are in medical solutions, remote-contactless biosensing, bedding solutions, wearable, and wellness services. Fullpower is seeking a passionate, team-oriented, and self-motivated Data Scientist interested in working on our next generation of products and algorithms and modeling rich, biomedical sensor data with a view toward medical, health, and fitness outcomes. The ideal candidate will have a strong background in machine learning and data science and a proven track record of deploying models and algorithms for real-world applications. Job Responsibilities: Work with health data and time-series sensor data Connect biomedical sensor data with medical, health, and fitness outcomes Research and development of machine learning algorithms and statistical models for non-invasive sleep tracking Develop visualizations and tools for understanding and annotating data Optimize algorithms for running on embedded devices and in the cloud Design and run experiments and clinical trials Processing, cleaning, and combining different data sources to create new datasets Collaborate with an interdisciplinary team of scientists, engineers, mathematicians for quick deployment of solutions Software skills: Expertise in Python and packages such as numpy, pandas, scikit-learn Experience with a deep learning framework such as Tensorflow, py Torch, or equivalent Experience working with databases including familiarity with SQL Experience with Amazon Web Services (AWS) or Google Cloud Experience with C++ is a plus Leadership qualities: Self starter Strong interpersonal and communication skills Education and Experience: Experience applying data science and machine learning to real-world problems Bachelor's degree or higher in Mathematics, Statistics, Physics, Computer Science, or equivalent Graduate degree and/or 5+ years experience a plus Additional Information: Fullpower does not sponsor work visas - must already be authorized to work in the United States The base salary range for this full-time position is $130,000 to $170,000, plus equity, plus benefits. Fullpower's salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education and training.

We are seeking a seasoned Data Scientist to collaborate closely with cross-functional teams. Your role will be pivotal in shaping our product strategy using robust scientific methodologies. Leveraging your expertise in statistical analysis, machine learning, and econometric modeling on extensive datasets, you will measure outcomes, identify causal impacts, predict future performance, and design innovative data-driven solutions. In this role, you will Partner across the company with Product, Engineering, Marketing, Sales, Finance and Data Science teams to shape product strategy using rigorous scientific solutions Apply statistical, machine learning and econometric models on large datasets to: measure results and outcomes identify causal impact and attribution predict future performance of users or products Design, implement and launch innovative data science solutions to empower data-driven decisions at scale Design, analyze, and interpret the results of experiments Develop key metrics and observability for Aven products Drive the collection of new data and the refinement of existing data sources Create analyses that tell compelling stories and inspire action We're looking for someone with 5+ years of data science experience with a track record of thought leadership and innovation A PhD or MS in a quantitative field (e.g., Engineering, Mathematics, Natural Sciences, or Economics) Expert knowledge of a scientific computing language (such as R or Python) and SQL Theoretical and applied expertise in statistics, machine learning and experimental design Excellent written and verbal communication skills Experience designing and implementing complex modeling solutions from ideation to production at scale Experience influencing high-impact decisions Strong project management and organizational skills

Established in 2017, WeRide (NASDAQ: WRD) is a leading global commercial-stage company that develops autonomous driving technologies from Level 2 to Level 4. WeRide is the only tech company in the world that holds driverless permits in China, the UAE, Singapore and the US, conducting autonomous driving R&D, tests and operations in over 30 cities of 10 countries around the world. WeRide has operated a self-driving fleet for more than 2,200 days. WeRide.ai Silicon Valley team is looking for an experienced and innovative data scientist for its growing metrics team to support the development and validation of both L3+ Advanced Driver Assistance Systems (ADAS) and L4 Autonomous Driving (AD) Systems. The level depends on the candidate's experience and qualification. The metrics team is at the forefront of accelerating the development and deployment of cutting-edge ADAS/AV technologies. As a Senior Data Scientist on this team, you will play a pivotal role in ensuring the safety, reliability, and efficiency of our autonomous systems. You will be responsible for developing and implementing rigorous evaluation frameworks and advanced statistical methodologies to assess overall system performance, as well as the performance of critical sub-systems across software releases, and different territories. Your work will directly inform crucial engineering decisions, guide iterative improvements, and contribute to the successful commercialization of our ADAS/AV stack. What You Will Do: * Develop Rigorous Evaluation Frameworks: Design, develop, and implement advanced statistical frameworks for the comprehensive evaluation of ADAS/AV system performance, with a strong emphasis on safety, compliance, and progress metrics. * Define and Monitor System Performance: Define, measure, and monitor key performance indicators (KPIs) for the overall ADAS/AV system. Develop automated data pipelines and reporting mechanisms to track these metrics across software releases. * Evaluate Sub-system Performance: Define and implement metrics to evaluate the performance of individual sub-systems. Utilize these metrics to provide actionable insights that guide and accelerate sub-system development and improvement. * Statistical Analysis and Experimentation: Apply advanced statistical techniques, including hypothesis testing, experimental design, and causal inference, to analyze complex behavioral data and derive robust insights into system performance and regressions between releases. * Partner with Engineering Teams: Collaborate closely with Simulation, Systems Engineering, Product, and Software Development teams to integrate evaluation insights into the development lifecycle, inform release readiness, and ensure alignment on performance targets. * Technical Leadership and Mentorship: Provide technical leadership on complex data science problems, champion best practices in data analysis and statistical rigor, and mentor junior data scientists within the team. * Data Visualization and Communication: Create compelling data visualizations and communicate complex analytical findings clearly and concisely to diverse audiences, ranging from technical engineers to senior leadership. Requirements: * Quantitative Degree: Master's degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field. * Extensive Industry Experience: 3+ years of industry experience solving complex data science problems, with a strong focus on building and applying rigorous analytical and statistical models. * Advanced Statistical Expertise: Deep expertise in advanced statistical methods and their application in real-world settings, including experimental design, hypothesis testing, regression analysis, causal inference and time series analysis, etc. * Technical Problem Formulation: Proven ability to translate ambiguous real-world challenges into clearly defined data science problems, identify appropriate methodologies, and deliver effective solutions. * Data Manipulation and Analysis: Proficiency in using programming languages (e.g., Python, R) and SQL for data extraction, manipulation, and analysis. * Communication: Excellent verbal and written communication skills, with the ability to tailor technical explanations to various stakeholders. * Flexibility: Ability to collaborate effectively with teams in different time zones. Preferred Qualifications: * PhD degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field. * 5+ years of industry experience solving complex data science problems, with a strong focus on building and applying rigorous analytical and statistical models. * Experience with large-scale evaluation frameworks for complex software systems, particularly in autonomous driving or robotics. * Familiarity with ADAS/AV system architectures and the behavioral challenges inherent in autonomous driving. * Knowledge of simulation platforms and their role in data generation and system evaluation. Salary Range: Your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $130,000 - $182,000 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. WeRide.ai offers competitive salary depending on the experience. Employee benefits include: Premium Medical, Dental and Vision Plan (No cost from employees or their families) Free Daily Breakfast, Lunch and Dinner Paid vacations and holidays 401K plan We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job DescriptionEstablished in 2017, WeRide (NASDAQ: WRD) is a leading global commercial-stage company that develops autonomous driving technologies from Level 2 to Level 4. WeRide is the only tech company in the world that holds driverless permits in China, the UAE, Singapore and the US, conducting autonomous driving R&D, tests and operations in over 30 cities of 10 countries around the world. WeRide has operated a self-driving fleet for more than 2,200 days. WeRide.ai Silicon Valley team is looking for an experienced and innovative data scientist for its growing metrics team to support the development and validation of both L3+ Advanced Driver Assistance Systems (ADAS) and L4 Autonomous Driving (AD) Systems. The level depends on the candidate's experience and qualification. The metrics team is at the forefront of accelerating the development and deployment of cutting-edge ADAS/AV technologies. As a Senior Data Scientist on this team, you will play a pivotal role in ensuring the safety, reliability, and efficiency of our autonomous systems. You will be responsible for developing and implementing rigorous evaluation frameworks and advanced statistical methodologies to assess overall system performance, as well as the performance of critical sub-systems across software releases, and different territories. Your work will directly inform crucial engineering decisions, guide iterative improvements, and contribute to the successful commercialization of our ADAS/AV stack. What You Will Do: Develop Rigorous Evaluation Frameworks: Design, develop, and implement advanced statistical frameworks for the comprehensive evaluation of ADAS/AV system performance, with a strong emphasis on safety, compliance, and progress metrics. Define and Monitor System Performance: Define, measure, and monitor key performance indicators (KPIs) for the overall ADAS/AV system. Develop automated data pipelines and reporting mechanisms to track these metrics across software releases. Evaluate Sub-system Performance: Define and implement metrics to evaluate the performance of individual sub-systems. Utilize these metrics to provide actionable insights that guide and accelerate sub-system development and improvement. Statistical Analysis and Experimentation: Apply advanced statistical techniques, including hypothesis testing, experimental design, and causal inference, to analyze complex behavioral data and derive robust insights into system performance and regressions between releases. Partner with Engineering Teams: Collaborate closely with Simulation, Systems Engineering, Product, and Software Development teams to integrate evaluation insights into the development lifecycle, inform release readiness, and ensure alignment on performance targets. Technical Leadership and Mentorship: Provide technical leadership on complex data science problems, champion best practices in data analysis and statistical rigor, and mentor junior data scientists within the team. Data Visualization and Communication: Create compelling data visualizations and communicate complex analytical findings clearly and concisely to diverse audiences, ranging from technical engineers to senior leadership. Requirements: Quantitative Degree: Master's degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field. Extensive Industry Experience: 3+ years of industry experience solving complex data science problems, with a strong focus on building and applying rigorous analytical and statistical models. Advanced Statistical Expertise: Deep expertise in advanced statistical methods and their application in real-world settings, including experimental design, hypothesis testing, regression analysis, causal inference and time series analysis, etc. Technical Problem Formulation: Proven ability to translate ambiguous real-world challenges into clearly defined data science problems, identify appropriate methodologies, and deliver effective solutions. Data Manipulation and Analysis: Proficiency in using programming languages (e.g., Python, R) and SQL for data extraction, manipulation, and analysis. Communication: Excellent verbal and written communication skills, with the ability to tailor technical explanations to various stakeholders. Flexibility: Ability to collaborate effectively with teams in different time zones. Preferred Qualifications: PhD degree in Data Science, Statistics, Mathematics, Engineering, Computer Science, or a related quantitative field. 5+ years of industry experience solving complex data science problems, with a strong focus on building and applying rigorous analytical and statistical models. Experience with large-scale evaluation frameworks for complex software systems, particularly in autonomous driving or robotics. Familiarity with ADAS/AV system architectures and the behavioral challenges inherent in autonomous driving. Knowledge of simulation platforms and their role in data generation and system evaluation. Salary Range: Your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $130,000 - $182,000 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package. WeRide.ai offers competitive salary depending on the experience. Employee benefits include:Premium Medical, Dental and Vision Plan (No cost from employees or their families) Free Daily Breakfast, Lunch and DinnerPaid vacations and holidays 401K plan We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Data Science Team within the Risk Data & AI Innovation Org. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis and loss mitigation. This position requires a person who has experience with machine learning, model development with cutting edge AI/ML frameworks, performing analytics, statistical analysis and model monitoring. Experience with LLMs and other AI tools would be a big plus. Wed love to chat if you have: 2-6 years of experience in machine learning/AI, data science, risk analytics & data analysis within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse. Bachelors/Master's degree in Data Science, Data Analytics, Mathematics, Statistics, Data Mining or related field or equivalent practical experience Experience using statistics and data science (machine learning & AI) to solve complex business problems Proficiency in SQL, Python, AWS, Excel including key data science libraries Proficiency in data visualization including Tableau Experience working with large datasets Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau. Comfortable with ambiguity and yet able to steer AI and machine learning projects toward clear business goals, testable hypotheses, and action-oriented outcomes Demonstrated analytical thinking through data-driven decisions, as well as the technical know-how, and ability to work with your team to make a big impact. Desirable to have experience or aptitude solving problems related to risk using data science and analytics Bonus: Experience with development and implementation of AI tools (e.g. LLMs) for risk use cases. Key Job Functions: Design and develop machine learning and AI models detect/mitigate fraud Support stakeholders and cross-functional teams in effective usage of models Drive AI transformation for all risk management activities at BILL Work with product/engineering to implement, monitor and refine AI solutions and models Expected Outcomes: Work closely with team members and stakeholders to consult, design, develop, and manage fraud models and AI solutions. Utilize data analysis to design and implement fraud models Collaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud models and AI solutions that operate at scale and in real time for end customers. Make business recommendations to leadership and cross-functional teams with effective presentations of findings at multiple levels of stakeholders. Development of dashboard and visualizations to track KPI of fraud models implemented Preferred Skills: Machine Learning & Artificial Intelligence Data Science Model development Dashboard Creation Project Management Strong Communication Skills. Notes from Hiring Manager: Strong SQL proficiency Experience applying statistics and data science to tackle intricate business challenges especially in Fraud mitigation Proficiency in AWS Quicksight and Tableau This is a hybrid position, so candidates must be based in the San Jose area. HM will entertain remote candidates if no viable local candidates can be sourced. Strictly contract to cover multiple leaves over a 1 yr. period. Potential to extend based on business need and performance. Day shift: M-F Pacific time Multiple Zoom interviews (2-3) SQL assessment during 1st interview. MUST HAVE: 2-6 years of experience in machine learning/AI, data science, risk analytics & data analysis within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse. Bachelors/Master's degree in Data Science, Data Analytics, Mathematics, Statistics, Data Mining or related field or equivalent practical experience Experience using statistics and data science (machine learning & AI) to solve complex business problems Proficiency in SQL, Python, AWS, Excel including key data science libraries Proficiency in data visualization including Tableau Experience working with large datasets Bonus: Experience with development and implementation of AI tools (e.g. LLMs) for risk use cases.

Did you know that Money Laundering is a primary enabler of criminal activity like drug trafficking, smuggling, terrorism, and corruption around the world with an estimated $2.3 Trillion laundered annually? Criminals are becoming more and more sophisticated in rapidly innovating new ways to launder money and current methods of detecting money laundering are antiquated and ineffective. Quantiply's Sensemaker application suite and platform solutions use AI and machine learning algorithms to identify money laundering and other criminal activities and automatically recommend mitigation strategies and actions. If you are looking for an opportunity to work on complex business problems using the latest AI and Machine Learning technologies, work with best and brightest in crafting innovative solutions while making a positive impact on society, Quantiply is the place for you. Job Description In this role, you will be part of a brand new, trend setting Cognitive Intelligence team which is applying Machine learning and AI to solve complex, business critical problems in the financial services industries. This position within the Cognitive Intelligence team presents a unique and rare opportunity to get in on the ground floor within a fast-growing business and help shape the technology, product, and business. As a real-time transactional intelligence service, our solutions have to be scalable, secure, efficient, and extremely fault-tolerant. A successful candidate will bring: deep technical and software expertise; ability to define visionary, ground breaking products; desire to have an industry-wide impact; and an ability to work within a fast moving, startup environment to rapidly deliver services that drive broad business impact. Responsibilities: Apply your expertise in designing, implementing and validating unsupervised deep learning, reinforcement learning and bayesian models. Present exploratory findings to both, technical and management teams, verbally and in writing. Partner with Product and Engineering teams to explore new opportunities. Engage in collaborating across team members to meet research and product goals. Influence product features and product roadmap through exploratory analysis. Qualifications Minimum qualifications: PhD in machine learning, statistics, engineering, mathematics, computer science, neuroscience, bioinformatics, game theory or other technical field. Strong knowledge of mathematics. Strong knowledge of machine learning and statistics. Strong knowledge of designing algorithms. Some experience in Python and Tensorflow. Preferred qualifications: Strong knowledge of deep learning. Strong knowledge of reinforcement learning. Strong experience in Tensorflow or similar frameworks. Working experience in C++. Additional Information All your information will be kept confidential according to EEO guidelines.

QuantumScape is on a mission to transform energy storage with solid-state lithium-metal battery technology. The company's next-generation batteries are designed to enable greater energy density, faster charging and enhanced safety to support the transition away from legacy energy sources toward a lower carbon future. About the team: Manufacturing Quality is a diverse group of engineers and data scientists who bring deep expertise in materials science, electrochemistry, statistics, and machine learning. Our team thrives on data-driven decision-making and a shared commitment to drive continuous improvement to QuantumScape's solid-state battery technology. We work closely with the Manufacturing, Reliability, and R&D, groups to identify failure modes, engineer critical-to-quality specifications, and implement robust control strategies across all process areas. What we need: The Manufacturing Quality team is seeking a mid-level engineer who is proficient with data science methodologies and is excited about improving the quality and reliability of our solid-state Li metal batteries. You will support specification development activities interfacing with multiple cross-functional departments across the company. The ideal candidate has a hard sciences background, statistics and data science experience through coursework or industry, and the ability to communicate complex technical information to a diverse group of stakeholders. If you enjoy problem-solving and thrive in a highly collaborative, fast-paced environment, we'd like to hear from you. What You'll do: * Design and implement new specifications based on in-line metrology inspection systems (e.g. optical, 3D, radiograph) across film, cathode, and cell assembly processes to drive improvements to the quality and reliability of our batteries. * Leverage machine learning or traditional statistics methodologies to identify in-process metrics that are best predictive of electrical performance. Identify strategy to increase cell reliability based on the learnings. * Develop machine learning models to classify components or features based on underlying knowledge. Coordinate labeling, development, validation, and implementation of models. * Define and validate statistically-valid sampling strategies to accept/reject batches based on measurements of a small subset of parts. * Communicate complex technical information to cross-functional stakeholders with refined presentations and weekly write-ups. Propose path forward based on learnings. * Continuously study state-of-the-art data science methodologies through AI-assisted literature review, critically identify best options, and rapidly apply them to internal projects. Skills You'll Need: * B.S. & 3+ years of experience or M.S. & 1+ years of experience is required. Educational background preferably in Materials Science, Chemical Engineering, Chemistry, Physics, or equivalent engineering field. * Strong programming skills with 2+ years of relevant experience through coursework or industry. * Proficiency with Python data science and machine learning libraries, such as Pandas, Scikit-learn, SciPy, TensorFlow, PyTorch, etc. * Proficiency with SQL to query data from database and data warehouse storage (i.e.: GCP's BigQuery) * Industry or academic experience with statistical analysis for manufacturing processes, like regression (i.e.: linear, logistics), t-tests, comparison of different test groups, etc. * Experience developing machine learning models such as tree-based models (i.e.: decision trees, random forest, XGBoost, etc.) or deep learning models (i.e.: neural networks, autoencoders, etc.) to predict binary or continuous outcomes using large, complex datasets. * Excellent written and verbal communication skills to collaborate closely with cross-functional colleagues. Nice to have: * 2+ years of experience in the battery manufacturing industry. * Hands-on experience with battery assembly, failure analysis, or characterization techniques. * Proficiency with AI coding tools to accelerate data analysis and visualization, model development, etc. * Proficiency with SQL to query data from database and data warehouse storage. * Proficiency with JMP, Microsoft Office, VSCode, and Github Copilot. Physical requirements: * Work is performed in an office. * Sitting or standing for extended periods of time. HYBRID: This position is required to work onsite at least 4 days per week to meet the minimum essential duties and requirements of this position. As a data scientist in the Manufacturing Quality team, in-person face-to-face interaction is essential to building authentic relationships, trust, teamwork, and collaboration. Compensation & Benefits: The expected salary range for this role is from $134,400 to $174,700, and a final salary will be determined by the candidate's experience and educational background. QuantumScape also offers an annual bonus and a generous RSU/Equity package as part of its compensation plan. In addition, we do offer a tremendous benefits plan including employee paid health care, Employee Stock Purchase Plan (ESPP), and other benefits. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive benefits and privileges of employment. Please contact us to request an accommodation. Nearest Major Market: San Jose Nearest Secondary Market: Palo Alto

Responsibilities: Work on small and large data sets of structured, semi-structured, and unstructured data to discover hidden knowledge about the client's business and develop methods to leverage that knowledge for their business. Identify and solve business challenges working closely with cross-functional teams, such as Delivery, Business Consulting, Engineering and Product Management. Develop prescriptive and predictive statistical, behavioral or other models via machine learning and/or traditional statistical modeling techniques, and understand which type of model applies best in a given business situation. Drive the collection of new data and the refinement of existing data sources. Analyze and interpret the results of product experiments. Collaborate with the engineering and product teams to develop and support our internal data platform to support ongoing statistical analyses. Qualifications A proven passion for generating insights from data. Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources. Expertise in mathematics and applied statistics, computer science, and visualization capabilities. Curious and an excellent learner. Able to research, explore and acquire working knowledge in new areas. A complete understanding of standard statistical techniques like MLE/QMLE, GMM, OLS/GLS, univariate and multivariate time series models (e.g. ARIMA, DLM's, VAR's), regression model diagnostics for time series and cross sectional data, along with Machine Learning methodologies like Random Forests, SVM's and Boosting/Bagging. The ideal candidate would know when and how to apply these alternative methodologies, and the relative advantages/disadvantages of each for a particular business case. Expert knowledge of an analysis tool/statistical package such as R, JMP, Stata, SPSS, SAS, Matlab Highly effective communicator; able to communicate complex quantitative analysis in a clear, precise & actionable way that is meaningful to general business audience and credible to client's data scientists. Fluency with at least one scripting language such as Python, Java, or C/C++. Expertise with relational databases and SQL. NoSQL is a big plus. REQUIREMENTS: MS or Ph.D. preferred in a quantitative Social Science (e.g. Economics) or Statistics with a substantive field interest. At least 5 years' experience in business, consulting or applied field research with project lead responsibilities for solving analytics problems using quantitative approaches. Demonstrated track record producing models and actionable insights using advanced statistical methods. Experience working with large data sets using distributed computing tools, e.g. Map/Reduce, Hadoop, Hive, etc. Additional Information All your information will be kept confidential according to EEO guidelines.

3MK Software Solutions is the leading software service soltions provider and IT Staffing Supplier company, outsourcing and complex implementation services for the business across different functional areas and technologies with a core focus on software development and web designing development and GIS Software solutions and services. Our team is our core strength, we have selected the most skilled and talented specialists from the IT industry, and we continuously invest in developing their capabilities. The core management has many years of experience and has successfully leaded complex projects for major corporate in the field of healthcare, communication, retail and finance. During the term of these projects, the team had needed to develop an advanced implementation methodology. Job Description JD: We are seeking a smart and engaged Data Scientist to work with our large data sets. As an intelligence connection & search-product oriented firm you can imagine the amount of data we're uncovering . We need your help developing advanced mathematical and statistical models to map data and deliver web analytics. Our product is widely utilized but is perhaps most useful in an academic and / or research capacity. · Natural Language Processing (NLP) , and Machine Learning · Minimum Required Skills: R, Python, SQL, SQL, Hadoop, Algorithms, Machine Learning, Data Mining · Data Scientist - machine learning & NLP modeling · Machine learning development and deployment · advanced NLP modeling · big data framework experience (Spark, MapReduce) · Bachelor's or Master's degree in Computer Science, Statistics, or Mathematics · Develop statistical modeling techniques for pattern recognition problems. · Develop code in Python, R, and SQL, or other object oriented languages for modeling optimization, simulation, and statistical analysis. · Build models that maximize performance and accuracy · Strategic planning and project management. Additional Information All your information will be kept confidential according to EEO guidelines.

Our Employees Are Among The Most Talented People In Their Fields And The Key To Our Success At Samsung, we encourage our employees to showcase their talent through our diverse corporate culture. Our strength is our people. Each individual makes an impact to the company and plays a vital role in contributing to the company's success. Our employees are motivated and passionate. We foster innovative thinking through an enthusiastic work environment. Through synergistic collaboration with other brilliant minds, we build some of the most advanced technology. In order to retain our talented workforce, we provide an excellent benefits package. We encourage a healthy work-life balance so that our employees are satisfied and more productive. We focus on developing our employees by providing them with the right tools and empowering them to succeed. Employee development is a key component of the continuing growth of our business. Our employee development programs help to create a workforce that is well-rounded. Job Description We are seeking a data scientist with at least 1 year of experience working with large data sets and 10 years of total professional experience. This role is expected to translate business objectives into actionable data analysis and communicate findings clearly to technical and non-technical audiences. Qualifications Responsibilities: • Searching for data sets matching data analytics requirements; • Applying transformations to cleanse and shape data set prior to analysis; • Performing exploratory data analysis; • Applying techniques for selecting representative data set features ; • Defining the most suitable machine learning method based on data product requirements; • Applying statistical methods to solve domain problems; • Applying data sampling techniques; • Developing and testing statistical models; • Defining procedures for obtaining data, ensuring validity and accuracy; Collaborating with business units to elicit data analytics requirements; Skills: Required • Analytical thinking; • Understanding of statistics fundamentals; • In-depth knowledge on the Hadoop stack (Map reduce, HDFS, Hive, Pig); • In-depth knowledge on machine learning methods; • Experience with scripting languages such as Python; • Understanding of main statistical methods; • Understanding of sampling techniques; • Understanding of descriptive and inferential statistics concepts; • Business domain experience in one of the following areas: retail, enterprise mobility, healthcare; • B.Sc. degree in Computer Science, Engineering, Mathematics, Statistics or related field is required • M.Sc. degree in related field is desirable. Additional Information Tanya Danylevska Talent acqusition team Samsung SDSA [email protected]

Title: Data Scientist Level V / Machine Learning Engineer Level V Duration: 6 Months + With possible extension Onsite Requirement: No remote work, 3 days onsite Experience: 10+ Years HM Notes: This current team is consisting of 5 Data Engineers working on eBay Security data, which spans into Petabytes. They lack a Data Scientist / Machine Learning Engineer and seek someone to bridge this gap. The ideal candidate will assist the team in building Client models on Security Data. Mandatory Skills: Python as a Programming Language Very strong experience in building Client models Hadoop Experience Experience working with Security data & Fraud detection Dealt with a significant amount of Streaming Data Nice to have - Winning Combination: Experience in Generative AI Experience in security Software Development Experience in Real-Time Data Processing We request all candidates to provide a detailed summary answering the following question, which should be prominently displayed at the top of each submitted resume: "In his/her previous roles - What is the anomaly or a fraud case you were trying to solve using Client models? and how did you solve the problem statement? " Please prioritize sourcing top-notch quality resumes for this role and share them with me at your earliest convenience. Day to Day Responsibilities of this Position and Description of Project: Required Skill Sets: Experience with scientific computing language and big data knowledge, including Python, SQL, Hive, Hadoop, Spark etc. Experience with common machine learning algorithms (SVM, KNN, logistic regression, random forest, XGBoost, Neural Networks, etc.) Develop and maintain Client/Stats models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring. Developed skills in the application of scientific methods to practical problems through exploratory data analysis, hypothesis testing and data visualization to reach robust conclusions. Understanding of statistical probability distributions, bias, error and power as well as sampling and resampling methods. Expertise in the manipulation, integration, processing and interrogation of large datasets. Maintain data quality and support data access. Experience with source control tools such as GitHub and related CI/CD processes Ability to tackle ambiguous and undefined problems and thrive with minimal oversight and process. Ability to communicate and discuss complex topics with technical and non-technical audiences Better to have or willing to learn: Leverage data to inform strategic directions of safety signal development, aid in incident response, automate detection and enforcement, and provide intelligence on ecosystems. Operationalize and evolve Threat Detections metrics that measure the impact of our targeted enforcement. Feel comfortable with analyzing and telling stories of security, audit and network data, and understand the context of monitor systems and threat detection. Disseminate intelligence gathered to other safety stakeholders and executive decision makers.

Role: Data Scientist - Machine Learning Focus (This role is open to US Citizens, Green Card holders, GC-EAD only. We do not sponsor visas.) Adidev Technologies Inc ************************** Adidev Technologies is seeking 2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment. If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist / Data Analyst / Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients. Job Description • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation-systems, environmental systems and/or agronomic problems. • Strong foundation in Python programming in a cloud environment. • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills • Expertise in data wrangling using SQL, • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes • Fluency in querying/extracting/aggregating data via SQL scripting. • Extract, load and transform data (ETL) from structured and unstructured sources • Apply Natural Language Processing and Computer Vision to solve business use cases, • Strong skills in scientific data analyses, modeling, visualization and communication of results. • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction Must have • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others) • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization) • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM) • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.) • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.) • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest • Distributed computing tools and cloud technology (AWS) Benefits Competitive Salary Paid Relocation Remote Support Guaranteed Regular Salary Reviews Job Type: W2 or Contract 1099 (full-time - 40 hours). Ready to Embark? we invite you to take this extraordinary step with us. Showcase your journey in pushing the limits of mobile engineering by submitting your resume and a curated selection of your most influential projects. At Adidev Technologies, we're dedicated to shaping your success. Join us to craft a future powered by innovation and growth. Note: Adidev Technologies Inc. is a staunch advocate of diversity and equal opportunity. We warmly welcome applications from candidates of all backgrounds, experiences, and walks of life. Your unique perspective could be the catalyst for our next revolutionary breakthrough

We are looking for a data scientist that will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. Responsibilities Selecting features, building and optimizing classifiers using machine learning techniques Data mining using state-of-the-art methods Extending company's data with third party sources of information when needed Enhancing data collection procedures to include information that is relevant for building analytic systems Processing, cleansing, and verifying the integrity of data used for analysis Doing ad-hoc analysis and presenting results in a clear manner Creating automated anomaly detection systems and constant tracking of its performance