Data Science Engineer Jobs in California
Data Science Engineer jobs in California are among the most active in the country, concentrated in technology, finance, healthcare, and entertainment across seniority levels from entry-level analyst to principal engineer. San Francisco, Los Angeles, and San Diego anchor the bulk of hiring, with major employers such as Google, Apple, and Kaiser Permanente maintaining large data engineering teams throughout the state. The most in-demand specialties are machine learning infrastructure, real-time data pipelines, and AI platform engineering. Find a role that fits below and apply directly.
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About Allogene:
Allogene Therapeutics, with headquarters in South San Francisco, is a clinical-stage biotechnology company pioneering the development of allogeneic chimeric antigen receptor T cell (AlloCAR T) products for cancer and autoimmune disease. Led by a management team with significant experience in cell therapy, Allogene is developing a pipeline of “off-the-shelf” CAR T cell product candidates with the goal of delivering readily available cell therapy on-demand, more reliably, and at greater scale to more patients.
About the Role:
Allogene’s Manufacturing organization is building a world-class team that is focused on delivering potentially lifesaving therapies to patients. We are seeking a highly motivated individual to join us as a Data Science Engineer, Manufacturing Sciences and Technology. This role will have hands-on responsibility over all manufacturing process data, including ensuring robust data infrastructure, data collection and analysis, and establishing best data management practices. This role will directly support technical and strategic initiatives to advance process understanding, control and qualification activities from late-stage development through launch/commercialization. The position is based at Allogene’s manufacturing facility in Newark, CA.
Responsibilities include, but are not limited to:
- Ownership of data lake infrastructure, including data ingestion, cleaning, organization, visualization and integration with data analysis tools.
- Translate process understanding into data and develop data analysis methodology to inform process and quality decisions.
- Generate data packages to support PPQ-readiness, PPQ execution and BLA submission for allogeneic CAR-T therapies and critical starting materials.
- Able to apply and develop advanced technologies, scientific principles, theories and concepts to meet the needs of the Process Development and Manufacturing teams, including support of technology transfers.
- In-depth knowledge of GMP and regulatory expectations and experience with regulatory inspections.
- Work with Quality, Facilities & Engineering, Process Development and IT to ensure cross-functional alignment.
- Closely partner with the Process Development and Quality groups to ensure continuity of data, robust process design and monitoring of product quality.
- Contribute to company-wide AI initiatives as a thought leader for introduction and implementation of new AI tools for continuous improvement and innovation.
- Engage with broader manufacturing team to enable accomplishment of department goals.
- Other duties as assigned.
Position Requirements & Experience:
- Bachelor’s degree in science or engineering (with a focus on computer science or data science preferred) with a minimum of 6 years of experience within a GMP pharmaceutical manufacturing space and 2 years of direct data science experience within a GMP pharmaceutical manufacturing space.
- Late-stage clinical and commercial experience preferred.
- Proficiency in programming languages including SQL, Python and R and data analytics tools, including JMP, Spotfire, Tableau, R-Studio.
- Knowledge of pharmaceutical manufacturing processes and GMP requirements for data integrity. Cell therapy experience preferred.
- Experience developing and implementing data solutions with machine learning and AI preferred.
- Excellent written and verbal communication skills.
- Excellent organizational skills and an ability to prioritize effectively to deliver results within established timelines.
- Ability to work independently and as part of a team.
- Ability to travel up to 10%.
- Candidates must be authorized to work in the U.S.
We offer a chance to work with talented people in a collaborative environment and provide a top-notch compensation and benefits package, which includes an annual performance bonus, equity, health insurance, generous time off (including 2 annual holiday company-wide shutdowns) and much more. The expected salary range for this role is $120,000 to $140,000 per year. Actual pay will be determined based on experience, qualifications, geographic location, business needs, and other job-related factors permitted by law.
As an equal opportunity employer, Allogene is committed to a diverse workforce. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, gender, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job-related characteristics or other prohibited grounds specified in applicable federal, state and local laws. We also embrace differences in experience and background, and welcome diversity of opinions and thought, designed to create a stronger and better Allogene that is focused on developing life-changing products for patients.
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See All 3,795+ Data Science Engineer Jobs in California
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Find Data Science Engineer JobsData Science Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
Data Science Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
- Apple336

- NVIDIA179

- TikTok164

- ByteDance103

- Amazon95

Top Industries Hiring
- Technology & Software1,835
- Electronics & Hardware572
- Artificial Intelligence271
- Science & Research207
- Banking & Financial Services176
What California Employers Look For
The qualifications that appear most often in data science engineer jobs across California.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Proficiency in Python and SQL for data processing and model deployment pipelines
- Experience designing and maintaining large-scale distributed data systems or cloud infrastructure
- Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
- Demonstrated ability to build and monitor production-grade ETL or feature engineering pipelines
- Experience with cloud platforms such as AWS, Google Cloud, or Azure in a data engineering context
Data Science Engineer Jobs in California: Frequently Asked Questions
How do you become a data science engineer in California?
Data science engineering in California has no state-issued license or board exam, so the path runs through education and demonstrated technical skill. Most California employers expect at minimum a bachelor's degree in computer science, mathematics, or statistics, with many preferring a master's for senior roles. Building a portfolio of end-to-end projects covering data pipelines, model deployment, and cloud infrastructure is the practical differentiator California hiring teams look for most.
How much do data science engineers make in California?
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 data science engineers in California?
Employers hiring data science engineers in California right now include Apple, NVIDIA, and TikTok, based on current listings on Migrate Mate as of June 2026. California's concentration of technology headquarters, large health systems, and financial services firms means demand is distributed across both the Bay Area and Southern California year-round.
Which California cities have the most data science engineer jobs?
San Francisco, San Jose, and Santa Clara have the most data science engineer openings in California. The Bay Area leads because of its concentration of technology headquarters and AI-focused startups, while Los Angeles draws demand from the entertainment, media, and fintech sectors, and San Diego's presence of biotech and defense firms creates consistent openings there as well.
Are there remote data science engineer jobs in California?
Yes, and more than most fields. About 21% of data science engineer openings tied to California are remote or hybrid as of June 2026, reflecting how central data science engineering is to software-driven organizations that operate distributed teams. The portions of the role most commonly offered remotely are model development, pipeline architecture, and analytics engineering, while on-site expectations tend to apply to roles embedded in hardware, lab, or regulated healthcare environments.
How can I get hired as a data science engineer in California with little or no experience?
The most realistic entry path is moving from a closely adjacent role such as data analyst, machine learning engineer, or software engineer into a data science engineering function. Large California employers including technology companies and health systems like Kaiser Permanente run internship and new-graduate programs that feed directly into engineering tracks. Building a portfolio that demonstrates pipeline construction and model deployment in a cloud environment gives candidates without formal experience a concrete edge when applying to associate or junior engineer openings.
Where can I find and apply to data science engineer jobs in California?
You can find and apply to data science engineer jobs in California on Migrate Mate, which lists current California openings across industries and experience levels. Find the roles that fit your background and apply directly to the ones that match.
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