Senior Data Science Engineer Jobs in California
Senior Data Science Engineer jobs in California represent one of the most active markets in the country, concentrated in technology, healthcare, fintech, and entertainment sectors, with demand stretching from junior analysts through principal-level engineers. The largest hiring metros are San Francisco, Los Angeles, and San Diego, where companies like Google, Meta, and Kaiser Permanente maintain deep and ongoing data science teams. The most sought-after specializations in California right now are machine learning infrastructure, MLOps, and large language model deployment. Find a role that fits below and apply directly.
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Ready to be a Titan?
We're seeking a Director of Data Science for Operations to lead data science and applied AI across two connected domains: our operational core and the post-sales product experience. You'll partner with operations, finance, product, and engineering leadership to turn complex data into intelligent systems, decisions, and measurable impact—spanning internal operational efficiency and customer-facing AI products like support agents and onboarding. This is a player-coach leadership role: you'll set technical direction, build and develop a team, and own outcomes across both internal operations and in-product intelligence. This role has significant latitude to work on and invent new high ROI projects- the only limit is your creativity.
What You'll Do
- Own the data science and applied AI roadmap for operations—agentic systems, forecasting, lead scoring, voice of the customer aggregation, and decision-support that improve throughput, reliability, and unit economics. Build agents and AI workflows that don't just predict but act.
- Own the data science and AI behind post-sales product experiences, including the support agent, onboarding intelligence, and customer success automation—from design through production deployment, evaluation, and quality monitoring.
- Lead, hire, and develop a data science team executing on operational and product-facing work; set standards for technical rigor, evaluation, and production quality.
- Partner with operations, finance, and product leadership to identify high-leverage problems, frame them, and translate them into operational decisions and shipped AI capabilities.
- Drive the full lifecycle from problem definition through deployment and monitoring, ensuring systems hold up in production—whether powering an internal forecast, an autonomous workflow, or a live customer interaction.
- Establish metrics and evaluation frameworks connecting this work to operational, financial, and customer outcomes (e.g., deflection, resolution quality, time-to-value, retention), including rigorous evaluation of non-deterministic AI systems.
- Collaborate with data engineering, machine learning engineering, platform, and product teams on the infrastructure, data quality, orchestration, tooling, and guardrails these systems depend on.
- Communicate findings and recommendations to executive stakeholders, balancing technical depth with business clarity.
- Champion an AI/agent-first way of working within the team—both as a hands-on technical leader (e.g., Claude Code) and by inventing agentic systems that make the team faster.
What You'll Bring
- 8+ years in data science or applied AI/ML, with 5+ years leading and growing teams.
- Demonstrated track record deploying systems that delivered measurable impact—across both internal operational decisions and customer-facing AI features.
- Strong foundation in statistics and ML, plus depth in modern AI: LLMs, agentic systems, orchestration (e.g., tool use, MCP), retrieval, and the evaluation practices these require.
- Experience building or owning production AI systems—agents, conversational systems, or autonomous workflows—and the eval, monitoring, and safety practices they demand.
- Fluency in SQL and Python; familiarity with modern data and AI stacks (cloud warehouses, dbt, LLM/agent deployment pipelines).
- Proven ability to partner with non-technical executives and translate ambiguous business problems into tractable work.
- Comfort operating in a fast-moving, data-rich environment where decisions carry real operational, cost, and customer-experience consequences.
Nice to Have
- Background in B2B SaaS, marketplaces, logistics, or field operations.
- Familiarity with customer success, onboarding, or support operations as a domain.
Be Human With Us:
Being human isn’t about checking every box on a list. It’s about the experiences we have, people we meet, and the perspectives we share. So, if you have the skills but are hesitant to apply because of your background, apply anyway. We need amazing people like you to help us challenge the conventional and think differently about the problems that we’re solving. We’re in this together. Come be human, with us.
Use of AI Technology:
We use technology, including automated and AI-assisted tools, to support certain aspects of our recruitment process. These tools are designed to improve efficiency and enhance the candidate experience. AI tools are not used to make hiring decisions; all hiring decisions are made by our hiring teams.
What We Offer:
When you join our team, you’re not just accepting a job. You’re making a career move. Here’s how we’ll support you in doing some of the most impactful work of your career:
- Flextime, recognition, and support for autonomous work: Flexible time off with ample learning and development opportunities to continue growing your career. We offer a comprehensive onboarding program, leadership training for Titans at all levels, and other programs and events. Great work is rewarded through Bonusly, peer-nominated awards, and more.
- Holistic health and wellness benefits: Company-paid medical, dental, and vision (with 100% employer paid options and 90% coverage for dependents), FSA and HSA, 401k match, and telehealth options including memberships to One Medical.
- Support for Titans at all stages of life: Parental leave and support, up to $20k in fertility services (i.e. IUI and IVF), surrogacy, and adoption reimbursement, on demand maternity support through Maven Maternity, free breast milk shipping through Maven Milk, pet insurance, legal advisory services, financial planning tools, and more.
At ServiceTitan, we celebrate individuality and uniqueness. We believe that the convergence of fresh perspectives and experiences from all walks of life is what makes our product and culture so great. We strongly encourage people from underrepresented groups to apply. We do not discriminate against employees based on race, color, religion, sex, national origin, gender identity or expression, age, disability, pregnancy (including childbirth, breastfeeding, or related medical condition), genetic information, protected military or veteran status, sexual orientation, or any other characteristic protected by applicable federal, state or local laws.
See All 107+ Senior Data Science Engineer Jobs in California
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Find JobsSenior Data Science Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
Senior Data Science Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring



Top Industries Hiring
- Technology & Software24
- Electronics & Hardware4
- Biotechnology & Pharmaceuticals4
- Consulting & Professional Services4
- Retail3
What California Employers Look For
The qualifications that appear most often in senior data science engineer jobs across California.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Five or more years of experience in data science, machine learning, or data engineering
- Proficiency in Python and SQL with demonstrated production-level modeling experience
- Experience designing and deploying ML pipelines in cloud environments such as AWS or GCP
- Strong background in statistical modeling, experimentation, and A/B testing methodologies
- Ability to communicate complex findings clearly to both technical and non-technical stakeholders
Senior Data Science Engineer Jobs in California: Frequently Asked Questions
How do you become a senior data science engineer in California?
The path to a senior data science engineer role in California typically starts with a bachelor's or master's degree in computer science, statistics, mathematics, or a related field. California has no state-issued license or registration required for this role. Employers in California's tech and healthcare sectors look for candidates with a portfolio of deployed models, experience with large-scale data systems, and several years in progressively complex data or engineering roles before reaching senior level.
How much do senior data science engineers make in California?
Senior data science engineers in California earn a median of about $141,590 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $77,480 for the lowest 10% to over $224,920 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire senior data science engineers in California?
Employers hiring senior data science engineers in California right now include TikTok, Adobe, and Apple, based on current listings on Migrate Mate as of August 2026. California's dense concentration of technology headquarters, health systems, and financial services firms means hiring is distributed across the state rather than limited to a single industry cluster.
Which California cities have the most senior data science engineer jobs?
San Jose, San Francisco, and San Diego have the most senior data science engineer openings in California. The San Francisco Bay Area leads because of the concentration of major technology headquarters and venture-backed startups there, while Los Angeles draws demand from entertainment technology, e-commerce, and healthcare analytics firms, and San Diego's biotech and defense industries sustain a steady base of openings.
Are there remote senior data science engineer jobs in California?
Yes, and more than most fields. Senior data science engineering is well suited to remote and hybrid arrangements because the work centers on code, data pipelines, and analysis rather than physical presence. About 53% of senior data science engineer openings tied to California are remote or hybrid as of August 2026. The roles most commonly offered remotely are those focused on modeling, experimentation, and analytics, while positions involving on-site infrastructure or close cross-functional collaboration tend to require some in-office time.
How can I get hired as a senior data science engineer in California with little or no experience?
The most realistic entry path is building a portfolio of end-to-end projects that demonstrate modeling, data wrangling, and deployment skills, then targeting associate data scientist or data engineer roles at California employers. Large California-based technology companies and health systems run structured new-grad programs and rotational analyst tracks that feed into senior pipelines over time. Adjacent roles such as data analyst, business intelligence engineer, or machine learning researcher are common lateral entry points. Earning a cloud certification or completing a graduate program at a California university strengthens early-career applications considerably.
Where can I find and apply to senior data science engineer jobs in California?
You can find and apply to senior data science engineer jobs in California on Migrate Mate, which lists current California openings. Find roles that fit your experience and location, then apply directly to the employer through each listing.
See All 107+ Senior Data Science Engineer Jobs in California
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