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Data Science Developer Jobs in California (NOW HIRING)

Collaborate with engineering, product, power system experts, and external partners to translate high-level business goals into rigorous data science roadmaps. * Executive Communication: Persuasively ...

Collaborate with engineering, product, power system experts, and external partners to translate high-level business goals into rigorous data science roadmaps. * Executive Communication: Persuasively ...

Data Science Lead

Milpitas, CA · On-site +1

$148K - $168K/yr

Data Science Lead Job Code: A011.4794 Job Location: Milpitas, CA Job Type: Full-Time Rate of Pay ... Draw on a wide palette of optimization modeling, mathematics, statistics, AI/ML, and programming ...

The data science team is very much applied - their work directly makes its way into real products ... Data Engineering & Curation * Expertise in large-scale data collection, labeling, cleaning, and ...

Data Science Lead

Milpitas, CA · On-site

$148K - $168K/yr

Data Science Lead Job Code: A011.4794 Job Location: Milpitas, CA Job Type: Full-Time Rate of Pay ... Draw on a wide palette of optimization modeling, mathematics, statistics, AI/ML, and programming ...

Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap ... Act as a thought leader on emerging data science techniques (personalization, recommendation ...

Collaborate with Data Scientists, Data Engineers, and Product teams on ongoing initiatives. * Document analyses, methodologies, and project findings. * Participate in team meetings, knowledge-sharing ...

The Data Science Director will collaborate with Engineering and Product executives across Meta Ads and the Family of Apps Monetization teams. The candidate will have extensive experience in large ...

New

The Data Science Director will collaborate with Engineering and Product executives across Meta Ads and the Family of Apps Monetization teams. The candidate will have extensive experience in large ...

New

Data Science Manager

San Francisco, CA · On-site

$160K - $220K/yr

We're looking for a Data Science Manager to lead our growing AI product data science function. This ... You'll partner closely with Product, Engineering, and Platform teams to deliver fast-moving ...

Data Science Manager

Los Angeles, CA · On-site

$160K - $220K/yr

We're looking for a Data Science Manager to lead our growing AI product data science function. This ... You'll partner closely with Product, Engineering, and Platform teams to deliver fast-moving ...

Data Science Manager

Los Angeles, CA · On-site

$160K - $220K/yr

We're looking for a Data Science Manager to lead our growing AI product data science function. This ... You'll partner closely with Product, Engineering, and Platform teams to deliver fast-moving ...

Data Science Manager

San Francisco, CA · On-site

$160K - $220K/yr

We're looking for a Data Science Manager to lead our growing AI product data science function. This ... You'll partner closely with Product, Engineering, and Platform teams to deliver fast-moving ...

Collaborate with Data Scientists, Data Engineers, and Product teams on ongoing initiatives. * Document analyses, methodologies, and project findings. * Participate in team meetings, knowledge-sharing ...

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Data Science Developer information

See California salary details

$16

$56

$80

How much do data science developer jobs pay per hour?

As of Jul 20, 2026, the average hourly pay for data science developer in California is $56.07, according to ZipRecruiter salary data. Most workers in this role earn between $46.01 and $66.44 per hour, depending on experience, location, and employer.

What are some common challenges Data Science Developers face when integrating models into production environments?

Data Science Developers often encounter challenges in bridging the gap between developing models in experimental settings and deploying them into scalable, reliable production systems. Issues such as data inconsistencies, version control, and ensuring model reproducibility can arise. Additionally, collaborating effectively with DevOps and engineering teams to automate deployment pipelines and monitor model performance is crucial for long-term success. Understanding both machine learning and software engineering best practices helps overcome these hurdles and ensures smooth, efficient integration.

What is a Data Science Developer?

A Data Science Developer is a professional who combines expertise in programming, statistics, and data analysis to build models and algorithms that extract insights from large datasets. They often work with machine learning techniques, data visualization, and various data processing tools to solve business problems. Data Science Developers collaborate with other teams to design and implement data-driven solutions, and are skilled in languages like Python, R, or Scala. Their work is essential for organizations looking to leverage data for decision-making and innovation.

What are the key skills and qualifications needed to thrive as a Data Science Developer, and why are they important?

To thrive as a Data Science Developer, you need strong expertise in statistics, machine learning, programming (Python, R), and a background in computer science or a related quantitative field. Familiarity with data analysis tools (such as Pandas, NumPy, and scikit-learn), cloud platforms (like AWS or Azure), and experience with databases (SQL/NoSQL) are typically required, and certifications like Microsoft Certified: Azure Data Scientist Associate can be beneficial. Strong problem-solving skills, effective communication, and the ability to collaborate with cross-functional teams help you stand out. These skills are essential for building data-driven solutions that translate complex data into actionable business insights.

What is the difference between Data Science Developer vs Data Analyst?

AspectData Science DeveloperData Analyst
Required SkillsProgramming, machine learning, data modelingData visualization, statistical analysis, reporting
CertificationsData Science certifications, Python/R expertiseExcel, SQL, Tableau certifications
Work EnvironmentTech companies, startups, R&D teamsBusiness departments, marketing, finance
Job FocusDeveloping algorithms, predictive modelsInterpreting data, generating reports

While both roles analyze data, Data Science Developers focus on building models and algorithms to solve complex problems, often requiring programming and machine learning skills. Data Analysts primarily interpret existing data sets to generate insights and reports for business decisions. The roles overlap in data handling but differ in technical depth and objectives.

What are popular job titles related to Data Science Developer jobs in California? For Data Science Developer jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Science Developer jobs in California look for? The top searched job categories for Data Science Developer jobs in California are:
Infographic showing various Data Science Developer job openings in California as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $116,623 per year, or $56.1 per hour.
Data Science Manager

Data Science Manager

Tapestry

Mountain View, CA

Other

Medical, Dental, Vision, Retirement, PTO

Posted 23 days ago


Tapestry Inc. rating

8.0

Company rating: 8.0 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

1st of 104 rated fashion retailers


Job description

About Tapestry

Tapestry is a team within Alphabet working to build the AI-powered electric grid. We are tackling one of the world's most important infrastructure challenges: helping the energy system become more visible, understandable, reliable, affordable, abundant, and clean.

Originally born at X, Alphabet's moonshot factory, Tapestry brings together experts in energy, AI, software, engineering, and product to build tools that help the electricity ecosystem plan smarter, move faster, and operate more efficiently.

This is a global effort. Tapestry supports partners across the U.S., U.K., Chile, New Zealand, Australia, and Brazil as they work toward a cleaner, more resilient energy future.

Joining Tapestry means doing high-impact work with a multidisciplinary team tackling a problem that matters at global scale. Learn more about our team and our mission here.

About the role:

At Tapestry, data drives all our decision-making. Data Scientists work across the organization to help shape our business and technical strategies by processing, analyzing, and interpreting massive datasets. They lead our metrics assessment, analyze massive datasets and derive early insights, and partner with cross functional teams on the right datasets for maximum downstream impact. As a Data Science Manager, you will act as a pivotal technical leader to bridge the gap between complex business questions and advanced technical execution. You will build, mentor, and lead a high-performing team of data scientists to deliver operational excellence, accelerate product advancement, and drive business value.

In this role, you will deeply immerse yourself with the team of data scientists in data collection and analysis, develop compelling, synthesized recommendations for senior leadership, and be involved  to help drive implementation. Ultimately, your team's solutions will fundamentally improve electric grid visibility and resilience.

How you will contribute to the team...

1. Team Leadership and Strategic Delivery

  • People Management: Recruit, mentor, and lead a world-class team of data scientists. Cultivate talent through active technical mentorship and clear career development paths.
  • Cross-Functional Alignment: Collaborate with engineering, product, power system experts, and external partners to translate high-level business goals into rigorous data science roadmaps.
  • Executive Communication: Persuasively communicate your team's findings and strategic recommendations to senior executives and cross functional teams, tracking the long-term business impact of the solutions.

2. Data Integrity and Curation Strategy at Scale

  • Pipeline Oversight: Guide the team in discovering, investigating, and deriving insights from large and complex input datasets, both current and potential, from partners and other sources.
  • Gatekeeping Metrics: Oversee the definition of problem framing, test datasets, and core business, product and performance metrics that machine learning models will aim to optimize for.
  • Multi-Stage Quality Control: Ensure data integrity across the pipeline by establishing frameworks to assess intermediate datasets and metrics within multi-stage machine learning processes.
  • Annotation Rigor: Drive a comprehensive and scalable data annotation strategy that prioritizes quality through statistical rigor, ensuring data reliability for all downstream modeling.

3. Problem Definition and Advanced Analytics

  • Grid Visibility and Innovation: Lead the proactive exploration of new problem spaces to fundamentally improve electric grid visibility and resilience.
  • Experimentation Frameworks: Standardize how the team designs, executes, and analyzes A/B tests and other experiments to validate hypotheses and measure product impact.
  • Engineering Best Practices: Champion modern data science workflows, including the application of GenAI techniques for data analysis, ensuring the team follows robust engineering best practices.
What you should have...
  • PhD or Master's in a quantitative field and 8+ years of tech or energy industry work experience as a statistician, quantitative analyst, or data scientist. 
  • 5+ years of experience directly managing or leading high-performing data science and analytics teams, with a proven track record of delivering production-grade data solutions.
  • A proven track record of identifying where data science can add unique value during early product development, alongside a strong ability to influence other teams to collaborate on critical data science work.
  • Advanced skills in experimental design, including the ability to architect, guide, and validate robust A/B testing methodologies and statistical experiments in ambiguous environments.
  • Experience in Python, SQL, R, Pandas, Scikit-Learn, other ML frameworks as appropriate.
  • Experience with electric power grid data, and physics based understanding of electrical networks and utility data. Ability to bridge the gap between power systems and machine learning.
  • Experience in multivariate analysis, stochastic models, and sampling methods. Able to select the right statistical tool to solve for bias, variance, and data drift.
  • Applied experience with building comprehensive machine learning model evaluation tooling and processes on large datasets.
  • Proven ability to "zoom out" from complex technical details to build a cohesive product strategy, and "zoom in" to unblock technical hurdles.
  • Demonstrate strong collaboration with software engineering and cross functional teams to build ML-powered systems ready for production.
  • Exceptional storytelling abilities, with a knack for turning complex data pipelines and model metrics into clear business value for non-technical stakeholders.
Would be great to have...
  • Ability to thrive in ambiguity, set own goals and effectively delivering to them in a very fast-changing environment
  • Attention to detail, project management, and organizational skills
  • Fast learner with capacity to learn about a wide-spread of different technologies and industries
  • Passion for the energy and climate space
  • Track record of delivering scalable solutions to complex software problems
  • Experience in startup or high-growth environments

Tapestry Values:

  • Take charge: We take initiative and own outcomes that move the mission forward.
  • Transform with purpose: We build solutions that solve real problems and create meaningful impact.
  • Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
  • Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
  • Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.

What we offer:

A culture that supports growth, ownership, and meaningful impact, along with...

  • Competitive salary and equity
  • Medical, dental, and vision coverage
  • Generous PTO and flexible hybrid work model
  • 401(k) with employer contribution
  • Professional development
  • The ability to work on important real-world problems within an Alphabet-backed environment

The US base salary range for this full-time position is $207,000 - $304,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.


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