EY-Parthenon - Strategy and Execution - Growth Platforms - Data Scientist - Director
Ernst & Young Oman 4.7
Data scientist job in San Francisco, CA
Location: Atlanta, Boston, Chicago, Dallas, Denver, Detroit, Houston, Los Angeles, McLean, New York, Hoboken, Philadelphia, San Francisco, Seattle
At EY, we're all in to shape your future with confidence.
We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
EY-Parthenon - EY Growth Platforms - DataScientist - Director The opportunity
EY-Parthenon's unique combination of transformative strategy, transactions and corporate finance delivers real-world value - solutions that work in practice, not just on paper. Benefiting from EY's full spectrum of services, we've reimagined strategic consulting to work in a world of increasing complexity.
With deep functional and sector expertise, paired with innovative AI-powered technology and an investor mindset, we partner with CEOs, Boards, Private Equity and Governments every step of the way - enabling you to shape your future with confidence.
Within the EY-Parthenon service line, the EY Growth Platforms DataScientist Director will collaborate with Business Leaders, AI/ML Engineers, Project Managers, and other team members to design, build, and scale innovative AI solutions that power strategic growth initiatives and create enterprise value for F500 clients.
Your key responsibilities
The EY Growth Platforms DataScientist Director will play a critical role building and scaling our multi-source data pipelines- sourcing, merging, and transforming data assets that power high-visibility client engagements. This role will architect, clean, transform, and enrich data to power AI/ML-driven agents and dashboards, and collaborate with Business leaders and C-level executives to get hands‑on experience solving some of the most interesting and mission‑critical business questions with data.
Skills and attributes for success
Lead ingestion and ETL design for structured and semi‑structured data (CSV, JSON, APIs, Flat Files).
Understand schema, data quality, and transformation logic for multiple sources on a client‑by‑client like NAIC, NOAA, Google Trends, EBRI, Cannex, LIMRA, and internal client logs.
Design normalization and joining pipelines across vertical domains (insurance + consumer + economic data).
Build data access layers optimized for ML (feature stores, event streams, vector stores).
Define and enforce standards for data provenance, quality checks, logging, and version control.
Partner with AI/ML and Platform teams to ensure data is ML‑ and privacy‑ready (HIPAA, SOC2, etc.).
To qualify for the role you must have
A bachelor's degree in Business, Statistics, Economics, Mathematics, Engineering, Computer Science, Analytics, or other related field and 5 years of related work experience; or a graduate degree and approximately 3 years of related work experience.
Experience in data engineering or hybrid data science roles focused on pipeline scalability and schema management.
Expertise in cloud‑native data infrastructure (e.g., GCP/AWS, Snowflake, BigQuery, Databricks, Delta Lake).
Strong SQL/Python/Scala proficiency and experience with orchestration tools (Airflow, dbt).
Experience with merging and reconciling third‑party data (public APIs, vendor flat files, dashboards).
Comfort defining semantic layers and mapping unstructured/dirty datasets into usable models for AI/BI use.
Basic understanding of ML/feature pipelines and downstream modeling needs.
The ability and willingness to travel and work in excess of standard hours when necessary.
Ideally, you will have
Experience working in a startup and/or management/strategy consulting.
Knowledge of how to leverage AI tools in a business setting, including Microsoft Copilot.
Collaborative, problem‑solving, and growth‑oriented mindset.
What we look for
We're interested in passionate leaders with strong vision and a desire to stay on top of trends in the Data Science and Big Data industry. If you have a genuine passion for helping businesses achieve the full potential of their data, this role is for you.
What we offer you
At EY, we'll develop you with future‑focused skills and equip you with world‑class experiences. We'll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more.
We offer a comprehensive compensation and benefits package where you'll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $205,000 to $235,000. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
Join us in our team‑led and leader‑enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40‑60% of the time over the course of an engagement, project or year.
Under our flexible vacation policy, you'll decide how much vacation time you need based on your own personal circumstances. You'll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well‑being.
Are you ready to shape your future with confidence? Apply today.
EY accepts applications for this position on an on‑going basis.
For those living in California, please click here for additional information.
EY focuses on high‑ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.
EY | Building a better working world
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi‑disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.
EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY's Talent Shared Services Team (TSS) or email the TSS at ************************** .
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$205k-235k yearly 4d ago
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Staff Data Scientist - Sales Analytics
Harnham
Data scientist job in San Francisco, CA
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 DataScientist 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 datascientist 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.
$200k-250k yearly 2d ago
Senior Workday Data Consultant & Applications Lead
Capgemini 4.5
Data scientist job in San Francisco, CA
A leading consulting firm in San Francisco seeks a Senior Applications Consultant specializing in Workday Data Conversion. The ideal candidate will be certified in Workday HCM and have significant experience with data conversion processes. Responsibilities include translating business needs into technical designs, managing issues, and leading testing efforts. Candidates must possess a Bachelor's degree and a minimum of 6 years of experience, with at least 2 in a relevant role. This position requires valid US work authorization.
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$101k-134k yearly est. 19h ago
Data Scientist
Talent Software Services 3.6
Data scientist job in Novato, CA
Are you an experienced DataScientist with a desire to excel? If so, then Talent Software Services may have the job for you! Our client is seeking an experienced DataScientist 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 DataScientist 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 DataScientist 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.
$99k-138k yearly est. 3d ago
Senior Energy Data Engineer - API & Spark Pipelines
Medium 4.0
Data scientist job in San Francisco, CA
A technology finance firm in San Francisco is seeking an experienced Data Engineer. The role involves building data pipelines, integrating data across various platforms, and developing scalable web applications. The ideal candidate will have a strong background in data analysis, software development, and experience with AWS. The salary range for this position is between $160,000 and $210,000, with potential bonuses and equity.
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$160k-210k yearly 3d ago
Full-Stack Engineer: AI Data Editor
Hex 3.9
Data scientist job in San Francisco, CA
A cutting-edge data analytics firm in San Francisco is seeking a full-stack engineer to enhance user experiences and integrate AI tools within their platform. You will work on innovative projects that shape data interactions, collaborate with teams on product initiatives, and tackle UX challenges. Ideal candidates should possess 3+ years of software engineering experience, proficiency in React and Typescript, and a strong desire to work in AI development. This position offers a competitive salary and benefits, with a hybrid work model.
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$126k-178k yearly est. 19h ago
Founding ML Infra Engineer - Audio Data Platform
David Ai
Data scientist job in San Francisco, CA
A pioneering audio tech company based in San Francisco is searching for a Founding Machine Learning Infrastructure Engineer. In this role, you will build and scale the core infrastructure that powers cutting-edge audio ML products. You will lead the development of systems for training and deploying models. Candidates should have over 5 years of backend experience with strong skills in cloud infrastructure and machine learning principles. The company offers benefits like unlimited PTO and comprehensive health coverage.
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$110k-157k yearly est. 3d ago
Data/Full Stack Engineer, Data Storage & Ingestion Consultant
Eon Systems PBC
Data scientist job in San Francisco, CA
About us
At Eon, we are at the forefront of large-scale neuroscientific data collection. Our mission is to enable the safe and scalable development of brain emulation technology to empower humanity over the next decade, beginning with the creation of a fully emulated digital twin of a mouse.
Role
We're a San Francisco team collecting very large microscopy datasets and we need an expert to design and implement our end-to-end data pipeline, from high-rate ingest to multi-petabyte storage and downstream processing. You'll own the strategy (on-prem vs. S3 or hybrid), the bill of materials, and the deployment, and you'll be on the floor wiring, racking, tuning, and validating performance.
Our current instruments generate data at ~1+ GB/s sustained (higher during bursts) and the program will accumulate multiple petabyes total over time. You'll help us choose and implement the right architecture considering reliability and cost controls.
Outcomes (what success looks like)
Within 2 weeks: Implement an immediate data-handling strategy that reliably ingests our initial data streams.
Within 2 weeks: Deliver a documented medium-term data architecture covering storage, networking, ingest, and durability.
Within 1 month: Operationalize the medium-term pipeline in production (ingest → buffer → long-term store → compute access).
Ongoing: Maintain ≥95% uptime for the end-to-end data-handling pipeline after setup.
Responsibilities
Architect ingest & storage: Choose and implement an on-prem hardware and data pipeline design or a cloud/S3 alternative with explicit cost and performance tradeoffs at multi-petabyte scale.
Set up a sustained-write ingest path ≥1 GB/s with adequate burst headroom (camera/frame-to-disk), including networking considerations, cooling, and throttling safeguards.
Optimize footprint & cost: Incorporate on-the-fly compression/downsampling options and quantify CPU budget vs. write-speed tradeoffs; document when/where to compress to control $/PB.
Integrate with acquisition workflows ensuring image data and metadata are compatible with downstream stitching/flat-field correction pipelines.
Enable downstream compute: Expose the data to segmentation/analysis stacks (local GPU nodes or cloud).
Skills
5+ years designing and deploying high-throughput storage or HPC pipelines (≥1 GB/s sustained ingest) in production.
Deep hands-on with: NVMe RAID/striping, ZFS/MDRAID/erasure coding, PCIe topology, NUMA pinning, Linux performance tuning, and NIC offload features.
Proven delivery of multi-GB/s ingest systems and petabyte-scale storage in production (life-sciences, vision, HPC, or media).
Experience building tiered storage systems (NVMe → HDD/object) and validating real-world throughput under sustained load.
Practical S3/object-storage know-how (AWS S3 and/or on-prem S3-compatible systems) with lifecycle, versioning, and cost controls.
Data integrity & reliability: snapshots, scrubs, replication, erasure coding, and backup/DR for PB-scale systems.
Networking: ****25/40/100 GbE (SFP+/SFP28), RDMA/ RoCE/iWARP familiarity; switch config and path tuning.
Ability to spec and rack hardware: selecting chassis/backplanes, RAID/HBA cards, NICs, and cooling strategies to prevent NVMe throttling under sustained writes.
Ideal skills:
Experience with microscopy or scientific imaging ingest at frame-to-disk speeds, including Micro-Manager-based pipelines and raw-to-containerized format conversions.
Experience with life science imaging data a plus.
Engagement details
Contract (1099 or corp-to-corp); contract-to-hire if there's a mutual fit.
On-site requirement: You must be physically present in San Francisco during build-out and initial operations; local field work (e.g., UCSF) as needed.
Compensation: Contract, $100-300/hour
Timeline: Immediate start
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$110k-157k yearly est. 4d ago
Global Data ML Engineer for Multilingual Speech & AI
Cartesia
Data scientist job in San Francisco, CA
A leading technology company in San Francisco is seeking a Machine Learning Engineer to ensure the quality and coverage of data across diverse languages. You will design large-scale datasets, evaluate models, and implement quality control systems. The ideal candidate has expertise in multilingual datasets and a strong background in applied ML. This full-time role offers competitive benefits, including fully covered insurance and in-office perks, in a supportive team environment.
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$110k-157k yearly est. 19h ago
Staff Machine Learning Data Engineer
Backflip 3.7
Data scientist job in San Francisco, CA
Mechanical design, the work done in CAD, is the rate-limiter for progress in the physical world. However, there are only 2-4 million people on Earth who know how to CAD. But what if hundreds of millions could? What if creating something in the real world were as easy as imagining the use case, or sketching it on paper?
Backflip is building a foundation model for mechanical design: unifying the world's scattered engineering knowledge into an intelligent, end-to-end design environment. Our goal is to enable anyone to imagine a solution and hit “print.”
Founded by a second-time CEO in the same space (first company: Markforged), Backflip combines deep industry insight with breakthrough AI research. Backed by a16z and NEA, we raised a $30M Series A and built a deeply technical, mission-driven team.
We're building the AI foundation that tomorrow's space elevators, nanobots, and spaceships will be built in.
If you're excited to define the next generation of hard tech, come build it with us.
The Role
We're looking for a Staff Machine Learning Data Engineer to lead and build the data pipelines powering Backflip's foundation model for manufacturing and CAD.
You'll design the systems, tools, and strategies that turn the world's engineering knowledge - text, geometry, and design intent - into high-quality training data.
This is a core leadership role within the AI team, driving the data architecture, augmentation, and evaluation that underpin our model's performance and evolution.
You'll collaborate with Machine Learning Engineers to run data-driven experiments, analyze results, and deliver AI products that shape the future of the physical world.
What You'll Do
Architect and own Backflip's ML data pipeline, from ingestion to processing to evaluation.
Define data strategy: establish best practices for data augmentation, filtering, and sampling at scale.
Design scalable data systems for multimodal training (text, geometry, CAD, and more).
Develop and automate data collection, curation, and validation workflows.
Collaborate with MLEs to design and execute experiments that measure and improve model performance.
Build tools and metrics for dataset analysis, monitoring, and quality assurance.
Contribute to model development through insights grounded in data, shaping what, how, and when we train.
Who You Are
You've built and maintained ML data pipelines at scale, ideally for foundation or generative models, that shipped into production in the real world.
You have deep experience with data engineering for ML, including distributed systems, data extraction, transformation, and loading, and large-scale data processing (e.g. PySpark, Beam, Ray, or similar).
You're fluent in Python and experienced with ML frameworks and data formats (Parquet, TFRecord, HuggingFace datasets, etc.).
You've developed data augmentation, sampling, or curation strategies that improved model performance.
You think like both an engineer and an experimentalist: curious, analytical, and grounded in evidence.
You collaborate well across AI development, infra, and product, and enjoy building the data systems that make great models possible.
You care deeply about data quality, reproducibility, and scalability.
You're excited to help shape the future of AI for physical design.
Bonus points if:
You are comfortable working with a variety of complex data formats, e.g. for 3D geometry kernels or rendering engines.
You have an interest in math, geometry, topology, rendering, or computational geometry.
You've worked in 3D printing, CAD, or computer graphics domains.
Why Backflip
This is a rare opportunity to own the data backbone of a frontier foundation model, and help define how AI learns to design the physical world.
You'll join a world-class, mission-driven team operating at the intersection of research, engineering, and deep product sense, building systems that let people design the physical world as easily as they imagine it.
Your work will directly shape the performance, capability, and impact of Backflip's foundation model, the core of how the world will build in the future.
Let's build the tools the future will be made in.
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$126k-178k yearly est. 3d ago
Foundry Data Engineer: ETL Automation & Dashboards
Data Freelance Hub 4.5
Data scientist job in San Francisco, CA
A data consulting firm based in San Francisco is seeking a Palantir Foundry Consultant for a contract position. The ideal candidate should have strong experience in Palantir Foundry, SQL, and PySpark, with proven skills in data pipeline development and ETL automation. Responsibilities include building data pipelines, implementing interactive dashboards, and leveraging data analysis for actionable insights. This on-site role offers an excellent opportunity for those experienced in the field.
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$114k-160k yearly est. 2d ago
Senior Data Engineer: ML Pipelines & Signal Processing
Zendar
Data scientist job in Berkeley, CA
An innovative tech firm in Berkeley seeks a Senior Data Engineer to manage complex data engineering pipelines. You will ensure data quality, support ML engineers across locations, and establish infrastructure standards. The ideal candidate has over 5 years of experience in Data Science or MLOps, strong algorithmic skills, and proficiency in GCP, Python, and SQL. This role offers competitive salary and the chance to impact a growing team in a dynamic field.
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$110k-157k yearly est. 3d ago
Distinguished Data Engineer - Card Data
Capital One 4.7
Data scientist job in San Francisco, CA
Distinguished Data Engineers are individual contributors who strive to be diverse in thought so we visualize the problem space. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. Distinguished Engineers will significantly impact our trajectory and devise clear roadmaps to deliver next generation technology solutions.**About the Team:** Capital One is seeking a Distinguished Data Engineer, to work in our Credit Card Technology Data Engineering Team and build the future of financial services. We are a fast-paced, mission-driven group responsible for managing and leveraging petabytes of sensitive, real-time and batch data that powers everything from fraud detection models and personalized reward systems to regulatory compliance reporting. As a leader in Data Engineering, you won't just move data; you'll architect high-availability that directly influence millions of customer experiences and secure billions in transactions daily. You'll own critical data domains end-to-end, working cross-functionally with ML Scientists, Product Managers, and Business Analysts teams etc to solve complex, high-stakes problems with cutting-edge cloud technologies (like Snowflake, Kafka, and AWS). If you thrive on technical challenges, demand data integrity, and want your work to have a clear, measurable impact on the bank's core profitability and security, this is your team.This leader must have the ability to attract and recruit the industry's best talent, and simultaneously have the technical chops to ensure that we build compelling, customer-oriented solutions in an iterative methodology. Success in the role requires an innovative mind, a proven track record of delivering next generation software and data products, rigorous analytical skills, and a passion for delivering customer value through automation, machine learning and predictive analytics.**Our Distinguished Engineers Are:*** Deep technical experts and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices* Visionaries, collaborating on Capital One's toughest issues, to deliver on business needs that directly impact the lives of our customers and associates* Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community* Evangelists, both internally and externally, helping to elevate the Distinguished Engineering community and establish themselves as a go-to resource on given technologies and technology-enabled capabilities**Responsibilities:*** Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in* Strike the right balance between lending expertise and providing an inclusive environment where others' ideas can be heard and championed; leverage expertise to grow skills in the broader Capital One team* Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible* Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization* Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in an unified manner* Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One's Tech talent**Basic Qualifications:*** Bachelor's Degree* At least 7 years of experience in data engineering* At least 3 years of experience in data architecture* At least 2 years of experience building applications in AWS**Preferred Qualifications:*** Masters' Degree* 9+ years of experience in data engineering* 3+ years of data modeling experience* 2+ years of experience with ontology standards for defining a domain* 2+ years of experience using Python, SQL or Scala* 1+ year of experience deploying machine learning models* 3+ years of experience implementing big data processing solutions on AWS***Capital One will consider sponsoring a new qualified applicant for employment authorization for this position***Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
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$106k-144k yearly est. 2d ago
Lead Actuarial Analyst
Workers' Compensation Insurance Rating Bureau of California (Wcirb 4.1
Data scientist job in Santa Rosa, CA
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!
$72k-98k yearly est. 2d ago
Principal Data Scientist : Product to Market (P2M) Optimization
The Gap 4.4
Data scientist job in San Francisco, CA
About Gap Inc. Our brands bridge the gaps we see in the world. Old Navy democratizes style to ensure everyone has access to quality fashion at every price point. Athleta unleashes the potential of every woman, regardless of body size, age or ethnicity. Banana Republic believes in sustainable luxury for all. And Gap inspires the world to bring individuality to modern, responsibly made essentials.
This simple idea-that we all deserve to belong, and on our own terms-is core to who we are as a company and how we make decisions. Our team is made up of thousands of people across the globe who take risks, think big, and do good for our customers, communities, and the planet. Ready to learn fast, create with audacity and lead boldly? Join our team.
About the Role
Gap Inc. is seeking a Principal DataScientist with deep expertise in operations research and machine learning to lead the design and deployment of advanced analytics solutions across the Product-to-Market (P2M) space. This role focuses on driving enterprise-scale impact through optimization and data science initiatives spanning pricing, inventory, and assortment optimization.
The Principal DataScientist serves as a senior technical and strategic thought partner, defining solution architectures, influencing product and business decisions, and ensuring that analytical solutions are both technically rigorous and operationally viable. The ideal candidate can lead end-to-end solutioning independently, manage ambiguity and complex stakeholder dynamics, and communicate technical and business risk effectively across teams and leadership levels.
What You'll Do
* Lead the framing, design, and delivery of advanced optimization and machine learning solutions for high-impact retail supply chain challenges.
* Partner with product, engineering, and business leaders to define analytics roadmaps, influence strategic priorities, and align technical investments with business goals.
* Provide technical leadership to other datascientists through mentorship, design reviews, and shared best practices in solution design and production deployment.
* Evaluate and communicate solution risks proactively, grounding recommendations in realistic assessments of data, system readiness, and operational feasibility.
* Evaluate, quantify, and communicate the business impact of deployed solutions using statistical and causal inference methods, ensuring benefit realization is measured rigorously and credibly.
* Serve as a trusted advisor by effectively managing stakeholder expectations, influencing decision-making, and translating analytical outcomes into actionable business insights.
* Drive cross-functional collaboration by working closely with engineering, product management, and business partners to ensure model deployment and adoption success.
* Quantify business benefits from deployed solutions using rigorous statistical and causal inference methods, ensuring that model outcomes translate into measurable value
* Design and implement robust, scalable solutions using Python, SQL, and PySpark on enterprise data platforms such as Databricks and GCP.
* Contribute to the development of enterprise standards for reproducible research, model governance, and analytics quality.
Who You Are
* Master's or Ph.D. in Operations Research, Operations Management, Industrial Engineering, Applied Mathematics, or a closely related quantitative discipline.
* 10+ years of experience developing, deploying, and scaling optimization and data science solutions in retail, supply chain, or similar complex domains.
* Proven track record of delivering production-grade analytical solutions that have influenced business strategy and delivered measurable outcomes.
* Strong expertise in operations research methods, including linear, nonlinear, and mixed-integer programming, stochastic modeling, and simulation.
* Deep technical proficiency in Python, SQL, and PySpark, with experience in optimization and ML libraries such as Pyomo, Gurobi, OR-Tools, scikit-learn, and MLlib.
* Hands-on experience with enterprise platforms such as Databricks and cloud environments
* Demonstrated ability to assess, communicate, and mitigate risk across analytical, technical, and business dimensions.
* Excellent communication and storytelling skills, with a proven ability to convey complex analytical concepts to technical and non-technical audiences.
* Strong collaboration and influence skills, with experience leading cross-functional teams in matrixed organizations.
* Experience managing code quality, CI/CD pipelines, and GitHub-based workflows.
Preferred Qualifications
* Experience shaping and executing multi-year analytics strategies in retail or supply chain domains.
* Proven ability to balance long-term innovation with short-term deliverables.
* Background in agile product development and stakeholder alignment for enterprise-scale initiatives.
Benefits at Gap Inc.
* Merchandise discount for our brands: 50% off regular-priced merchandise at Old Navy, Gap, Banana Republic and Athleta, and 30% off at Outlet for all employees.
* One of the most competitive Paid Time Off plans in the industry.*
* Employees can take up to five "on the clock" hours each month to volunteer at a charity of their choice.*
* Extensive 401(k) plan with company matching for contributions up to four percent of an employee's base pay.*
* Employee stock purchase plan.*
* Medical, dental, vision and life insurance.*
* See more of the benefits we offer.
* For eligible employees
Gap Inc. is an equal-opportunity employer and is committed to providing a workplace free from harassment and discrimination. We are committed to recruiting, hiring, training and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We have received numerous awards for our long-held commitment to equality and will continue to foster a diverse and inclusive environment of belonging. In 2022, we were recognized by Forbes as one of the World's Best Employers and one of the Best Employers for Diversity.
Salary Range: $201,700 - $267,300 USD
Employee pay will vary based on factors such as qualifications, experience, skill level, competencies and work location. We will meet minimum wage or minimum of the pay range (whichever is higher) based on city, county and state requirements.
$201.7k-267.3k yearly 56d ago
Staff Data Scientist - Experimentation & Measurement
Playstation 4.8
Data scientist job in San Mateo, CA
Why PlayStation?
PlayStation isn't just the Best Place to Play - it's also the Best Place to Work. Today, we're recognized as a global leader in entertainment producing The PlayStation family of products and services including PlayStation 5, PlayStation 4, PlayStation VR, PlayStation Plus, acclaimed PlayStation software titles from PlayStation Studios, and more.
PlayStation also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.
The PlayStation brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Group Corporation.
Staff DataScientist - Experimentation & Measurement
San Mateo, CA (Hybrid)
Overview:
As a Staff DataScientist on the Decision Science team at PlayStation, you will take a leading role in designing and interpreting experiments that evaluate the impact of key initiatives and programs. You'll help shape how millions of players around the world experience PlayStation by bringing statistical rigor, clear measurement strategies, and deep causal inference expertise to some of the most critical initiatives across the company. This highly visible role will advance our experimentation practices and ensure that data-driven insights inform the way we build, market, and evolve our products.
What You'll Be Doing:
Design, execute, and interpret A/B tests and quasi-experiments, and apply advanced causal inference methods when experimentation isn't feasible.
Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles and communicate results with the company's senior leadership.
Mentor and guide other DataScientists, providing thought leadership and technical direction.
Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results communication.
Help define and contribute to centralized experimentation frameworks, tools, and documentation to scale best practices across the company.
Independently extract, transform, and analyze data from complex systems using SQL, Python, and other analytics tools.
Communicate findings clearly to technical and non-technical stakeholders, helping drive business decisions with rigor and clarity.
Stay current on new methodologies in experimentation and causal analysis, and bring fresh perspectives to the team's work.
Your insights will directly influence how PlayStation builds, markets, and evolves products across our ecosystem.
Basic Requirements:
Master's or PhD in Statistics, Economics, or Econometrics.
6+ years of experience in a data science experimentation/causal inference-focused role (4+ with PhD).
Deep expertise in A/B testing and causal inference, including quasi-experimental methods.
Proficiency in SQL and Python for data extraction, transformation, and analysis.
Broad and applied knowledge of statistical techniques.
Experience with machine learning modeling is a plus.
Proven ability to influence product and business decisions through clear, actionable insights.
Experience contributing to or developing experimentation frameworks, best practices, or internal tooling.
Bonus: Passion for video games, player communities, or the gaming industry.
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Please refer to our Candidate Privacy Notice for more information about how we process your personal information, and your data protection rights.
At SIE, we consider several factors when setting each role's base pay range, including the competitive benchmarking data for the market and geographic location.
Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location.
In addition, this role is eligible for SIE's top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more.
The estimated base pay range for this role is listed below.$212,200-$318,200 USD
Equal Opportunity Statement:
Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.
We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.
PlayStation is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.
$212.2k-318.2k yearly Auto-Apply 11d ago
Director, Growth Platforms Data Scientist
Ernst & Young Oman 4.7
Data scientist job in San Francisco, CA
A leading global consulting firm seeks a DataScientist - Director in San Francisco to drive AI solutions and data initiatives. The ideal candidate will lead multi-source data pipelines, architect complex data solutions while collaborating with business leaders. Candidates should have a strong educational background, extensive experience in data engineering, and proficiency with SQL and cloud-native infrastructure. This role offers a competitive salary range of $205,000 to $235,000 and promotes a hybrid working model.
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$205k-235k yearly 4d ago
Staff Data Scientist - Post Sales
Harnham
Data scientist job in San Francisco, CA
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 datascientist 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.
$200k-250k yearly 2d ago
Senior Applications Consultant - Workday Data Consultant
Capgemini 4.5
Data scientist job in San Francisco, CA
Job Description - Senior Applications Consultant - Workday Data Consultant (054374)
Senior Applications Consultant - Workday Data Consultant
Qualifications & Experience:
Certified in Workday HCM
Experience in Workday data conversion
At least one implementation as a data consultant
Ability to work with clients on data conversion requirements and load data into Workday tenants
Flexible to work across delivery landscape including Agile Applications Development, Support, and Deployment
Valid US work authorization (no visa sponsorship required)
6‑8 years overall experience (minimum 2 years relevant), Bachelor's degree
SE Level 1 certification; pursuing Level 2
Experience in package configuration, business analysis, architecture knowledge, technical solution design, vendor management
Responsibilities:
Translate business cases into detailed technical designs
Manage operational and technical issues, translating blueprints into requirements and specifications
Lead integration testing and user acceptance testing
Act as stream lead guiding team members
Participate as an active member within technology communities
Capgemini is an Equal Opportunity Employer encouraging diversity and providing accommodations for disabilities.
All qualified applicants will receive consideration without regard to race, national origin, gender identity or expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status, or any other characteristic protected by law.
Physical, mental, or environmental demands may be referenced. Reasonable accommodations will be considered where possible.
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$101k-134k yearly est. 19h ago
Senior Data Engineer, Card Data Platform
Capital One 4.7
Data scientist job in San Francisco, CA
A financial services company in San Francisco seeks a Distinguished Data Engineer to lead innovation in data architecture and management. The role involves building critical data solutions, mentoring teams, and leveraging cloud technologies like AWS. Ideal candidates will have significant experience in data engineering, a Bachelor's degree, and proficiency in modern data practices to drive customer value through analytics and automation.
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How much does a data scientist earn in Petaluma, CA?
The average data scientist in Petaluma, CA earns between $92,000 and $183,000 annually. This compares to the national average data scientist range of $75,000 to $148,000.