Senior Data Science Engineer Jobs in San Francisco, CA
Senior Data Science Engineer jobs in San Francisco are concentrated in SoMa, the Financial District, and Mission Bay, driven by demand from tech platforms, fintech firms, and life sciences companies. Employers hiring right now include Lyft, Stitch Fix, and Adobe. See the openings below and apply to the ones that match your experience.
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About Stitch Fix, Inc.
Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we're equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what's possible for our clients, while we help you reach your full potential.
About the Role
The Client Experience Product Algorithms team is responsible for the machine learning, AI, experimentation, and product analytics capabilities that power personalized experiences for Stitch Fix clients and stylists. Partnering across Product, Engineering, Design, Styling, Marketing, Merchandising, Finance, Enterprise Analytics, Data Platform, and DSN, the team translates data and algorithms into measurable business impact.
As Director, Product Algorithms, you will lead the strategy, execution, and people behind our Growth, Styling, and Fix & Freestyle Algorithms portfolios. You'll define how AI, machine learning, experimentation, and analytics shape the future of personalized shopping while building the operating discipline, technical excellence, and cross-functional alignment needed to deliver scalable business results.
Responsibilities
- Lead the Product Algorithms portfolio across Growth, Styling, and Fix & Freestyle, setting strategy and driving measurable outcomes across acquisition, engagement, retention, styling quality, Fix, Freestyle, outfitting, and related commerce experiences.
- Define the vision and roadmap for applying data science, machine learning, AI, experimentation, and product analytics to improve client experiences, stylist effectiveness, and business performance.
- Drive innovation by identifying, evaluating, and scaling modern AI, machine learning, personalization, and experimentation techniques that create meaningful impact while balancing technical feasibility, execution capacity, and business priorities.
- Strengthen organizational effectiveness by improving planning, prioritization, experimentation practices, product analytics capabilities, operational readiness, incident management, and cross-functional decision making across the portfolio.
- Build and develop a high-performing organization of managers and senior individual contributors, fostering technical excellence, strong product leadership, accountability, and collaborative partnerships while representing Product Algorithms with executive stakeholders.
How AI and Tools Show Up in Your Day-to-Day Work
- Use AI-powered tools (such as ChatGPT, GitHub Copilot, and other emerging technologies) to improve decision making, productivity, communication, and operational efficiency.
- Leverage experimentation platforms, analytics tools, machine learning infrastructure, and product development systems to guide roadmap decisions and measure business impact.
- Continuously evaluate and adopt new AI capabilities, technologies, and ways of working that improve team effectiveness and accelerate innovation.
About You
You are a strategic technical leader who combines deep expertise in machine learning and AI with exceptional product thinking, organizational leadership, and business judgment. You thrive in highly collaborative environments, enjoy solving ambiguous problems, and know how to translate emerging technologies into measurable customer and business outcomes.
Requirements
- Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related quantitative field; advanced degree preferred.
- 10+ years of experience in data science, machine learning, experimentation, product analytics, AI, or algorithmic product development, including 5+ years leading teams and experience managing managers or senior technical leaders.
- Demonstrated success defining strategy and delivering production machine learning, AI, personalization, or experimentation capabilities that drive measurable product and business outcomes.
- Strong technical fluency across modern machine learning, generative AI/LLMs, experimentation methodologies, product analytics, and production algorithmic systems.
- Experience building cross-functional partnerships with Product, Engineering, Design, Analytics, Data Platform, Marketing, Merchandising, Finance, and executive stakeholders.
- Exceptional strategic thinking, communication, prioritization, problem-solving, and organizational leadership skills, with the ability to influence across technical and non-technical audiences.
- Experience using AI tools (such as ChatGPT, GitHub Copilot, or similar technologies) to improve productivity, decision making, collaboration, and the quality of work.
- This position requires the ability to sit for extended periods of time, use a computer and standard office equipment, and communicate effectively in both written and verbal formats.
Nice to Have
- Advanced degree (MS or PhD) in Computer Science, Machine Learning, Statistics, Operations Research, Engineering, or a related field.
- Experience leading AI- or ML-driven consumer products within e-commerce, marketplaces, retail, recommendations, personalization, or digital consumer experiences.
- Experience building or evolving experimentation platforms, product analytics capabilities, or AI governance and operational excellence practices.
- Familiarity with large-scale recommendation systems, ranking models, generative AI applications, causal inference, optimization, or reinforcement learning.
- Experience leading organizations through significant technical transformation, organizational scaling, or AI adoption initiatives.
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Find JobsSenior Data Science Engineer Job Market in San Francisco
Who's Hiring
- Lyft11

- Stitch Fix11

- Adobe6

- Figma6

- Gusto6

Top Industries Hiring
- Technology & Software45
- Retail6
- Fintech6
- Science & Research6
- Marketing & Advertising6
Senior Data Science Engineer Jobs in San Francisco: Frequently Asked Questions
How do I get a senior data science engineer job in San Francisco?
Focus your search on SoMa, Mission Bay, and the Financial District, where tech platforms, fintech firms, and biotech companies concentrate their data science teams. Candidates who stand out in San Francisco typically combine production-level ML experience with strong Python or Scala skills and can show measurable business impact. Networking through local data science meetups and contributing to open-source projects visible to Bay Area employers also gives you a concrete edge.
Which companies hire senior data science engineers in San Francisco?
Employers hiring senior data science engineers in San Francisco right now include Lyft, Stitch Fix, and Adobe, based on current listings on Migrate Mate as of August 2026. San Francisco's market includes a broad mix of late-stage startups, established tech giants, and financial services firms, all maintaining active data science teams.
Are there remote senior data science engineer jobs in San Francisco?
Yes, senior data science engineer roles are well-suited to remote and hybrid arrangements because the work is primarily analytical and code-based rather than on-site. About 85% of senior data science engineer openings tied to San Francisco are remote or hybrid as of August 2026, reflecting the tech sector's continued flexibility. Modeling, experimentation, and pipeline development are the functions most commonly performed remotely by San Francisco-based teams.
How can I get a senior data science engineer job in San Francisco with little or no experience?
The most realistic entry path in San Francisco is securing a junior data scientist or data analyst role at a mid-size tech company in SoMa or the Financial District and building toward senior-level ownership within two to three years. Early-career candidates gain traction by contributing to well-documented projects on GitHub, completing relevant Kaggle competitions, or landing contract work through San Francisco's active startup ecosystem. Targeting growth-stage startups, which often promote quickly, can accelerate your path to a senior title.
Which industries hire the most senior data science engineers in San Francisco?
Most senior data science engineer openings in San Francisco sit in Technology & Software, Retail, and Fintech, per current listings on Migrate Mate as of August 2026. San Francisco's density of tech platforms, fintech companies, and life sciences organizations drives consistent demand for senior data science talent across these sectors.
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