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Data Science Project Manager Jobs in California (NOW HIRING)

Samba

Director Data Science, Measurement

San Francisco, CA · On-site

$200K - $250K/yr

Own end-to-end delivery across the team's measurement science portfolio - managing dependencies ... Track record of owning and delivering complex, multi-workstream data science projects on time in a ...

Tapestry

Data Science Manager

Mountain View, CA · On-site

Data Scientists work across the organization to help shape our business and technical strategies by ... Attention to detail, project management, and organizational skills * Fast learner with capacity to ...

Tapestry

Data Science Manager

Mountain View, CA · On-site

Data Scientists work across the organization to help shape our business and technical strategies by ... Attention to detail, project management, and organizational skills * Fast learner with capacity to ...

Staffingine LLC

Senior Data Scientist

Los Angeles, CA · On-site

Design develop and deploy machine learning models and algorithms using Python Lead data science projects from concept to implementation ensuring timely delivery and quality outcomes * Perform ...

Omnicom

Director, Data Science

Los Angeles, CA · On-site

... project management skills with an ability to set and achieve goals, meet deadlines and act with a strong sense of urgency without compromising executional excellence Leverage technical (coding ...

Omnicom

Director, Data Science

Los Angeles, CA · Hybrid

... project management skills with an ability to set and achieve goals, meet deadlines and act with a strong sense of urgency without compromising executional excellence Leverage technical (coding ...

UC Davis Health

Senior Data Scientist

Sacramento, CA · On-site

$116K - $241K/yr

Hands-on data science problem solving with real-world, complex data sets. Experience applying ... Familiarity with project management and process improvement principles, concepts, and methodologies.

Heluna Health

Data Scientist Supervisor

Alhambra, CA · On-site

$9.8K - $13K/mo

JOB QUALIFICATIONS The ideal candidate is a seasoned data science professional with strong leadership skills, a track record of managing data science projects, and the ability to translate complex ...

Heluna Health

Data Scientist Supervisor

Alhambra, CA · On-site

$9.8K - $13K/mo

JOB QUALIFICATIONS The ideal candidate is a seasoned data science professional with strong leadership skills, a track record of managing data science projects, and the ability to translate complex ...

Whatnot

Manager, Data Science

San Francisco, CA · On-site

Role We're looking for a Manager, Data Science to lead a high-impact team working on core marketplace problems. In this role, you'll own measurement, experimentation, and analytical strategy across ...

Whatnot

Manager, Data Science

San Francisco, CA · On-site

$221K - $320K/yr

Role We're looking for a Manager, Data Science to lead a high-impact team working on core marketplace problems. In this role, you'll own measurement, experimentation, and analytical strategy across ...

Heluna Health

Data Scientist Supervisor

Alhambra, CA · On-site

$9.8K - $13K/mo

JOB QUALIFICATIONS The ideal candidate is a seasoned data science professional with strong leadership skills, a track record of managing data science projects, and the ability to translate complex ...

DoorDash

Manager, Data Science

San Francisco, CA · On-site

About the Role We're hiring two Data Science Managers, each to lead a pod within Merchant Analytics and help shape high-priority product and business decisions. In this role, you will lead a team of ...

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Data Science Project Manager information

See California salary details

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How much do data science project manager jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for data science project manager in California is $56.75, according to ZipRecruiter salary data. Most workers in this role earn between $49.09 and $66.44 per hour, depending on experience, location, and employer.

What is a data science project manager?

A Data Science Project Manager is a professional who oversees and coordinates data science projects from inception to completion. They act as a bridge between technical data science teams and business stakeholders, ensuring that project goals align with organizational objectives. Responsibilities include planning project timelines, managing resources, mitigating risks, and communicating progress. They also help define project requirements, monitor deliverables, and ensure that outcomes meet quality standards. Strong communication, analytical, and organizational skills are essential for this role.

How does a data science project manager typically collaborate with data scientists and stakeholders throughout a project?

A Data Science Project Manager acts as a bridge between technical teams and business stakeholders, ensuring clear communication of goals, timelines, and deliverables. They facilitate regular meetings to discuss project progress, address any obstacles, and realign priorities as needed. By translating business requirements into actionable tasks for data scientists and providing updates to stakeholders, they help ensure that projects stay on track and deliver value. Effective collaboration often involves balancing technical feasibility with business needs, managing expectations, and fostering a cooperative team environment.

What are the key skills and qualifications needed to thrive as a data science project manager, and why are they important?

To thrive as a Data Science Project Manager, you need a solid understanding of data science methodologies, project management principles, and usually a degree in computer science, statistics, or a related field. Familiarity with analytics tools (such as Python, R, SQL), project management software (like Jira or Trello), and certifications such as PMP or Agile/Scrum are often required. Strong leadership, communication, and problem-solving skills set top performers apart by enabling effective team coordination and stakeholder management. These competencies ensure projects are delivered on time, within scope, and generate actionable insights that drive business value.

What is the difference between Data Science Project Manager vs Data Analyst?

AspectData Science Project ManagerData Analyst
Required CredentialsOften requires a bachelor’s or master’s in data science, analytics, or related fields; project management certifications beneficialTypically holds a bachelor’s degree in statistics, mathematics, or related areas; certifications like Microsoft Excel or Tableau are common
Work EnvironmentLeads data science projects, collaborates with data scientists, engineers, and stakeholdersAnalyzes data sets, creates reports, visualizations, and supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms managing data science initiativesFound across industries for data reporting, business intelligence, and operational analysis

In summary, a Data Science Project Manager oversees data science projects and manages teams, requiring project management skills and relevant certifications. A Data Analyst focuses on analyzing data and creating reports, with a more technical and analytical role. Both roles are essential in data-driven organizations but differ in scope and responsibilities.

What are popular job titles related to Data Science Project Manager jobs in California?

For Data Science Project Manager jobs in California, the most frequently searched job titles are:

What job categories do people searching Data Science Project Manager jobs in California look for?

The top searched job categories for Data Science Project Manager jobs in California are:

What cities in California are hiring for Data Science Project Manager jobs?

Cities in California with the most Data Science Project Manager job openings:

Data Science Project Manager jobs near you
Infographic showing various Data Science Project Manager job openings in California as of August 2026, with employment types broken down into 90% Full Time, 9% Part Time, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $118,050 per year, or $56.8 per hour.

Director Data Science, Measurement

Samba

San Francisco, CA • On-site

$200K - $250K/yr

Full-time

Re-posted 12 hours ago

Job description

Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant. 

Reporting to our VP of Data Science, Samba is looking for a Director of Data Science to lead our Measurement science team - the group responsible for building the statistical frameworks, causal models, and attribution methodologies that power Samba's core measurement products. You will own the science and delivery for a portfolio spanning incrementality measurement, multi-touch attribution, reach and frequency modeling, and audience intelligence, working closely with Product to shape direction and with Engineering to bring solutions to production.

You are a senior technical leader first. You bring deep, hands-on expertise in causal ML, statistical modeling, and measurement science - enough to drive architectural decisions, mentor senior data scientists, and engage credibly in design reviews. You also know how to build and run a high-performing team, communicate clearly to executive and external audiences, and keep complex multi-workstream delivery on track.

WHAT YOU'LL DO

  • Measurement Science Strategy: Partner with Product to define the measurement science roadmap - spanning incrementality, multi-touch attribution, reach/frequency estimation, panel calibration, and audience targeting. Translate business and client priorities into well-scoped quarterly plans and sprint commitments.

  • Technical Leadership: Lead design reviews and architecture decisions across the team. Drive the application of Causal ML - counterfactual modeling, meta-learners, and heterogeneous treatment effect estimation - as the primary framework for measuring ad effectiveness, alongside rigorous command of the broader toolkit: A/B testing, DiD, synthetic control, Bayesian hierarchical models, and panel methodology.

  • Delivery & Execution: Own end-to-end delivery across the team's measurement science portfolio - managing dependencies, removing blockers, and ensuring timely delivery of high-quality work across multiple concurrent workstreams.

  • Scientific Standards & Data Quality: In partnership with Engineering, set and maintain standards for experimental design, model evaluation, reproducibility, and production readiness. Co-own the data quality framework that ensures the robustness and consistency of measurement products used by clients and internal stakeholders.

  • Best Practices & MLOps: In partnership with Engineering, develop and implement best practices for the full DS lifecycle - data management, modeling, evaluation, pipeline orchestration, and production deployment on Databricks/Spark.

  • People & Team Leadership: Lead, mentor, and grow a team of data scientists - owning hiring, performance reviews, career development, and individual goal-setting aligned to Samba's leveling framework. Build a high-accountability culture grounded in technical rigor, psychological safety, and continuous learning.

  • Cross-functional Partnership: Collaborate with Product, Engineering, and Business Development to define and execute data-driven measurement projects. Support Sales and Marketing with technical positioning and clear articulation of Samba's measurement capabilities.

  • Stakeholder Communication: Translate complex causal and statistical findings into clear, actionable insights for technical and non-technical audiences. Represent the team to senior leadership and external stakeholders, and contribute a credible technical voice to client conversations and industry forums.

WHO YOU ARE

  • 8+ years of hands-on data science experience with at least 2-3 years in a people management role, including demonstrated ability to hire, develop, and retain senior data scientists

  • Deep, first-principles expertise in Causal ML - counterfactual modeling, meta-learners, and heterogeneous treatment effect estimation - applied to advertising measurement or media outcomes; familiarity with EconML, DoWhy, or CausalML a plus

  • Solid command of the broader measurement science toolkit: A/B testing, difference-in-differences, synthetic control, propensity scoring, Bayesian hierarchical models, and panel methodology - with clear intuition for when to apply each approach and what its limitations are

  • Strong statistical and ML foundations - regression, classification, experimental design, model evaluation, and the ability to reason clearly about trade-offs between modeling approaches

  • Expert-level Python and SQL; strong PySpark and Databricks experience for large-scale measurement pipelines

  • Track record of owning and delivering complex, multi-workstream data science projects on time in a fast-moving environment

  • Excellent communicator - able to translate causal and statistical reasoning into language that drives product, sales, and executive decisions

  • Bachelor's degree required in Statistics, Computer Science, Mathematics, or a related quantitative field; Master's or PhD strongly preferred

  • Direct experience with TV or digital measurement - ACR/STB data, viewership panels, reach/frequency modeling, or cross-platform measurement (linear + CTV/OTT)

  • Hands-on experience with multi-touch attribution (MTA) or multi-channel attribution modeling - understanding of rule-based limitations and the methodological trade-offs of data-driven alternatives

  • Familiarity with the measurement vendor landscape (Nielsen, Comscore, VideoAmp, iSpot) and industry standards (MRC accreditation, GRP/TRP frameworks)

  • Experience with audience segmentation, identity resolution, or privacy-preserving measurement approaches

  • Track record of publishing research, white papers, or presenting at industry conferences

Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.  We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.
 
Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU , Samba Inc. is the data controller.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.