Data Science Engineer Jobs in San Francisco, CA
Data Science Engineer jobs in San Francisco are concentrated in SoMa, Mission Bay, and the Financial District, with strong demand across enterprise technology, fintech, and biotech. Employers actively hiring include Lyft, Stitch Fix, and Adobe. See the openings below and apply to the ones that match your experience.
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Showing 5 of 106+ Data Science Engineer jobs
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.
This link leads to the machine readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts between health plans and healthcare providers. The machine-readable files are formatted to allow researchers, regulators, and application developers to more easily access and analyze data.
Please review Stitch Fix's US Applicant Privacy Policy and Notice at Collection here: https://stitchfix.com/careers/workforce-applicant-privacy-policy
Recruiting Fraud Alert:
To all candidates: your personal information and online safety are top of mind for us. At Stitch Fix, recruiters only direct candidates to apply through our official career pages at https://www.stitchfix.com/careers/jobs or https://web.fountain.com/c/stitch-fix.
Recruiters will never request payments, ask for financial account information or sensitive information like social security numbers. If you are unsure if a message is from Stitch Fix, please email careers@stitchfix.com.
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.
This link leads to the machine readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts between health plans and healthcare providers. The machine-readable files are formatted to allow researchers, regulators, and application developers to more easily access and analyze data.
Please review Stitch Fix's US Applicant Privacy Policy and Notice at Collection here: https://stitchfix.com/careers/workforce-applicant-privacy-policy
Recruiting Fraud Alert:
To all candidates: your personal information and online safety are top of mind for us. At Stitch Fix, recruiters only direct candidates to apply through our official career pages at https://www.stitchfix.com/careers/jobs or https://web.fountain.com/c/stitch-fix.
Recruiters will never request payments, ask for financial account information or sensitive information like social security numbers. If you are unsure if a message is from Stitch Fix, please email careers@stitchfix.com.
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Find Data Science Engineer JobsData 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
Data Science Engineer Jobs in San Francisco: Frequently Asked Questions
How do I get a data science engineer job in San Francisco?
Focus your search on San Francisco's technology and fintech corridors, where the heaviest hiring concentrates in SoMa, Mission Bay, and around Salesforce Tower. Startups in the Dogpatch and growth-stage companies in the Financial District also hire consistently. Candidates who combine strong ML engineering skills with experience deploying models at scale stand out in this market, and familiarity with the cloud-native stacks common at Bay Area product companies gives a meaningful edge.
Which companies hire data science engineers in San Francisco?
San Francisco data science engineer roles are posted by Lyft, Stitch Fix, and Adobe and others right now, based on current listings on Migrate Mate as of August 2026. San Francisco's employer mix skews toward product-led technology firms, AI-native startups, and financial services companies that maintain engineering hubs in the city itself.
Are there remote data science engineer jobs in San Francisco?
Yes, data science engineering is well-suited to remote and hybrid arrangements given that the work is largely analytical and code-based rather than on-site or equipment-dependent. About 85% of data science engineer openings tied to San Francisco are remote or hybrid as of August 2026, reflecting how broadly Bay Area employers have adopted flexible models. Model training, pipeline development, and research roles are most frequently offered with remote flexibility.
How can I get a data science engineer job in San Francisco with little or no experience?
The most realistic entry path in San Francisco is through junior or associate data engineering roles at mid-size technology companies and fintech firms that actively invest in developing early-career talent. Many San Francisco companies also hire from university research partnerships and fellowship programs at local institutions. Building a public portfolio of end-to-end ML pipelines and contributing to open-source projects referenced by Bay Area employers can compensate for limited professional experience and gets attention from engineering hiring teams.
Which industries hire the most data science engineers in San Francisco?
The sectors hiring the most data science engineers in San Francisco are Technology & Software, Retail, and Fintech, based on current listings on Migrate Mate as of August 2026. San Francisco's role as a hub for enterprise software, AI development, and financial technology means those industries maintain high and consistent demand for engineering talent with a strong data and machine learning foundation.
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