Data Science Director Jobs in San Francisco, CA
Data Science Director jobs in San Francisco are concentrated in SoMa, the Financial District, and Mission Bay, where technology platforms, financial services firms, and life sciences companies generate strong and consistent demand for senior data leaders. Employers hiring right now include Adobe, Lyft, and GoFundMe. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 32+ Data Science Director jobs
About us
Beast Industries is a multifaceted media and entertainment company founded by Jimmy Donaldson, popularly known as MrBeast, the most watched person in the world. Renowned for revolutionizing digital content creation, Beast Industries encompasses a diverse portfolio of ventures that extend far beyond its origins on YouTube. With a mission to entertain, inspire, and create significant social impact, Beast Industries operates across various domains including digital media, philanthropy, consumer products, and innovative business initiatives. At Beast Industries, we believe in the transformative power of digital media and its potential to entertain, educate, and effect positive change. Our commitment to innovation, creativity, and philanthropy drives us to explore new frontiers, create unforgettable experiences, and build a legacy that inspires future generations.
Data Science Engineer
Primary: Bay Area (San Francisco / Peninsula) | Secondary: NYC
The Opportunity
We're doing an AI-first engineering rebuild for a company that already has an audience of 100M+ people. This is a zero-to-one build with no legacy constraints, so the models and data systems you ship define the foundation instead of patching an old one. You're here to turn ambiguous, high-stakes business problems into models that actually move a number in production.
The Product
You'll be the senior technical anchor for a data science domain, owning the full lifecycle from framing the problem through deployment, monitoring, and iteration. The work spans consumer products, media, and fintech analytics, all sitting on top of an audience of 100M+ people. That means:
- Frame vague business problems as tractable data science problems, and pick the approach and evaluation criteria when there's little precedent.
- Design, build, and deploy models and the data pipelines that feed and serve them in production.
- Build the monitoring and retraining framework that catches drift before it hits the business.
- Own the full model lifecycle: data sourcing and quality, features, training, evaluation, deployment, monitoring, and retraining.
- Set and enforce the domain's standards for validation, reproducibility, experimentation, and monitoring.
- Partner with engineering to productionize models reliably, with the right latency, scale, and observability.
- Translate model behavior and its limits for product and business stakeholders, including where data science can't help.
- Anticipate the failure modes (leakage, drift, bias, fragility) and build safeguards before they reach production.
- Guide the technical work of other data scientists and engineers through design review, pairing, and mentorship.
- Evaluate and adopt new methods and tooling, weighing innovation against maintainability and cost.
Who You Are
- AI-Native: You're already burning through tokens and using AI in your daily workflow to move faster from idea to shipped model.
- Production ML Builder: Typically 8+ years designing, building, and deploying ML models in production, with deep expertise in statistical modeling and sound judgment about method selection under uncertainty.
- End-to-End Owner: You've owned problems start to finish with limited supervision and been accountable for the result, not just the experiment.
- Honest Communicator: You frame problems as testable hypotheses, hold the line on validation rigor under deadline pressure, and communicate uncertainty honestly instead of overselling. Strong software engineering practice: production-quality code, version control, testing, and reproducible pipelines. Bonus points for setting technical direction for a data science domain, MLOps tooling for deployment and monitoring, and domain exposure in consumer products, media, or fintech.
Benefits
- Equity: Highly competitive equity package designed for a foundational hire.
- Hybrid Model: Expected: 3 days per week in-office (Bay Area or NYC).
The Perks — Why Work On the MrBeast Team
We are redefining what entertainment and storytelling look like at global scale. Every piece of content we publish reaches millions and influences culture in real time. This is your opportunity to join the team that decides how those moments come to life across every screen.
- Competitive Salary
- Generous Medical (Blue Cross Blue Shield), Dental, Vision and company-paid Life Insurance
- Company contributions to employee Health Savings Accounts (HSA)
- 401k Plan with Safe Harbor company-matching
- Flexible vacation policy and paid company holidays
- Company-provided technology package
- Relocation assistance where applicable, including travel and company-provided housing for the first 90 days
Come build the future of the creator ecosystem with us.
About us
Beast Industries is a multifaceted media and entertainment company founded by Jimmy Donaldson, popularly known as MrBeast, the most watched person in the world. Renowned for revolutionizing digital content creation, Beast Industries encompasses a diverse portfolio of ventures that extend far beyond its origins on YouTube. With a mission to entertain, inspire, and create significant social impact, Beast Industries operates across various domains including digital media, philanthropy, consumer products, and innovative business initiatives. At Beast Industries, we believe in the transformative power of digital media and its potential to entertain, educate, and effect positive change. Our commitment to innovation, creativity, and philanthropy drives us to explore new frontiers, create unforgettable experiences, and build a legacy that inspires future generations.
Data Science Engineer
Primary: Bay Area (San Francisco / Peninsula) | Secondary: NYC
The Opportunity
We're doing an AI-first engineering rebuild for a company that already has an audience of 100M+ people. This is a zero-to-one build with no legacy constraints, so the models and data systems you ship define the foundation instead of patching an old one. You're here to turn ambiguous, high-stakes business problems into models that actually move a number in production.
The Product
You'll be the senior technical anchor for a data science domain, owning the full lifecycle from framing the problem through deployment, monitoring, and iteration. The work spans consumer products, media, and fintech analytics, all sitting on top of an audience of 100M+ people. That means:
- Frame vague business problems as tractable data science problems, and pick the approach and evaluation criteria when there's little precedent.
- Design, build, and deploy models and the data pipelines that feed and serve them in production.
- Build the monitoring and retraining framework that catches drift before it hits the business.
- Own the full model lifecycle: data sourcing and quality, features, training, evaluation, deployment, monitoring, and retraining.
- Set and enforce the domain's standards for validation, reproducibility, experimentation, and monitoring.
- Partner with engineering to productionize models reliably, with the right latency, scale, and observability.
- Translate model behavior and its limits for product and business stakeholders, including where data science can't help.
- Anticipate the failure modes (leakage, drift, bias, fragility) and build safeguards before they reach production.
- Guide the technical work of other data scientists and engineers through design review, pairing, and mentorship.
- Evaluate and adopt new methods and tooling, weighing innovation against maintainability and cost.
Who You Are
- AI-Native: You're already burning through tokens and using AI in your daily workflow to move faster from idea to shipped model.
- Production ML Builder: Typically 8+ years designing, building, and deploying ML models in production, with deep expertise in statistical modeling and sound judgment about method selection under uncertainty.
- End-to-End Owner: You've owned problems start to finish with limited supervision and been accountable for the result, not just the experiment.
- Honest Communicator: You frame problems as testable hypotheses, hold the line on validation rigor under deadline pressure, and communicate uncertainty honestly instead of overselling. Strong software engineering practice: production-quality code, version control, testing, and reproducible pipelines. Bonus points for setting technical direction for a data science domain, MLOps tooling for deployment and monitoring, and domain exposure in consumer products, media, or fintech.
Benefits
- Equity: Highly competitive equity package designed for a foundational hire.
- Hybrid Model: Expected: 3 days per week in-office (Bay Area or NYC).
The Perks — Why Work On the MrBeast Team
We are redefining what entertainment and storytelling look like at global scale. Every piece of content we publish reaches millions and influences culture in real time. This is your opportunity to join the team that decides how those moments come to life across every screen.
- Competitive Salary
- Generous Medical (Blue Cross Blue Shield), Dental, Vision and company-paid Life Insurance
- Company contributions to employee Health Savings Accounts (HSA)
- 401k Plan with Safe Harbor company-matching
- Flexible vacation policy and paid company holidays
- Company-provided technology package
- Relocation assistance where applicable, including travel and company-provided housing for the first 90 days
Come build the future of the creator ecosystem with us.
See All 32 Data Science Director Jobs in San Francisco
Find roles in San Francisco that match your experience and apply in just a few clicks.
Find Data Science Director JobsData Science Director Job Market in San Francisco
Who's Hiring
- Adobe5
- Lyft3
- GoFundMe2
- Genentech2
- Stitch Fix2
Top Industries Hiring
- Technology & Software21
- Retail3
- Fintech2
- Medical Devices2
- Distribution & Wholesale2
Data Science Director Jobs in San Francisco: Frequently Asked Questions
How do I get a data science director job in San Francisco?
Focus your search on San Francisco's technology platforms, fintech firms, and biotech companies in Mission Bay and SoMa, where demand for senior data leaders is heaviest. Employers here favor candidates with demonstrated experience leading cross-functional data teams, a record of translating model output into product or revenue decisions, and familiarity with the fast iteration cycles common in San Francisco's product-driven companies. Prior work at a recognizable Bay Area employer helps significantly.
Which companies hire data science directors in San Francisco?
San Francisco data science director roles are posted by Adobe, Lyft, and GoFundMe and others right now, based on current listings on Migrate Mate as of June 2026. San Francisco's hiring pool is especially deep among consumer technology platforms, enterprise software companies, and growth-stage startups backed by prominent venture firms headquartered in the city.
Are there remote data science director jobs in San Francisco?
Yes, though remote availability is more common for directors whose work centers on modeling, analytics strategy, and stakeholder reporting than for those overseeing embedded engineering or lab-adjacent teams. About 67% of data science director openings tied to San Francisco are remote or hybrid as of June 2026, reflecting the analytical nature of most roles here. Strategy-heavy and product-analytics-focused positions tend to offer the most location flexibility.
How can I get a data science director job in San Francisco with little or no experience?
The most realistic path is moving into a senior individual contributor role at a mid-size San Francisco technology or fintech company first, then building into people management from within. Growth-stage startups in SoMa and the Financial District frequently promote strong senior data scientists into director-level roles faster than large established employers. Demonstrating ownership of a data initiative end-to-end, even on a small team, matters more than tenure to many San Francisco hiring managers.
Which industries hire the most data science directors in San Francisco?
Most data science director openings in San Francisco sit in Technology & Software, Retail, and Fintech, per current listings on Migrate Mate as of June 2026. San Francisco's concentration of consumer technology platforms, payments and fintech companies, and a growing Mission Bay biotech corridor creates sustained demand for senior data leadership across all three sectors.
Related Jobs in California
See All 32 Data Science Director Jobs in San Francisco
Find roles in San Francisco that match your experience and apply in just a few clicks.
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