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Data Science Physics Jobs in California (NOW HIRING)

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

D. in quantitative fields (e.g., Statistics, Math, Computer Science, Physics, Economics, Operational Research or Engineering) Company : Databricks is a data and AI platform that unifies data ...

P-57 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems ... D. in quantitative fields (e.g., Statistics, Math, Computer Science, Physics, Economics ...

Data Science * Statistics * Mathematics * Engineering ... Economics * Physics * Or a related quantitative field. We may use artificial intelligence (AI ...

Data Scientists work across the organization to help shape our business and technical strategies by ... Experience with electric power grid data, and physics based understanding of electrical networks ...

Data Scientists work across the organization to help shape our business and technical strategies by ... Experience with electric power grid data, and physics based understanding of electrical networks ...

Data Science Engineer

Livermore, CA ยท On-site

$121K - $154K/yr

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Physics, or a related technical field. * Experience with Python programming and software development ...

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Data Science Physics information

See California salary details

$24K

$90.6K

$196.3K

How much do data science physics jobs pay per year?

As of Jul 28, 2026, the average yearly pay for data science physics in California is $90,571.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,617.00 and $134,644.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Science Physics position, and why are they important?

To thrive in Data Science Physics, you need strong analytical abilities in both physics and statistics, typically supported by an advanced degree in physics, data science, or a related field. Familiarity with tools such as Python, MATLAB, machine learning libraries (e.g., scikit-learn, TensorFlow), and experience using simulation or data visualization software are essential. Excellent problem-solving, collaboration, and communication skills help you work effectively with multidisciplinary teams and explain complex findings to non-experts. These competencies enable efficient analysis and interpretation of large scientific datasets, driving innovation and informed decision-making in research and industry settings.

What does a typical day look like for someone working in Data Science Physics?

A typical day in Data Science Physics often involves collecting, cleaning, and analyzing large datasets derived from experimental or simulated physics research. You may spend time developing and testing predictive models, interpreting results, and visualizing data to communicate findings to colleagues and stakeholders. Collaboration is common, with regular meetings alongside scientists, engineers, and data professionals to discuss project goals or troubleshoot challenges. Additionally, you may contribute to research publications or help develop new methodologies for data analysis, making each day varied and intellectually stimulating.

What is a Data Science Physics job?

A Data Science Physics job combines physics principles with data science techniques to analyze complex datasets, build predictive models, and extract insights. Professionals in this role apply statistical methods, machine learning, and computational algorithms to solve problems in areas such as material science, astrophysics, and engineering. They often work with big data, simulations, and experimental data to improve decision-making and research outcomes.

What are the most commonly searched types of Data Science Physics jobs in California? The most popular types of Data Science Physics jobs in California are:
What are popular job titles related to Data Science Physics jobs in California? For Data Science Physics jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Science Physics jobs in California look for? The top searched job categories for Data Science Physics jobs in California are:
What cities in California are hiring for Data Science Physics jobs? Cities in California with the most Data Science Physics job openings:
Infographic showing various Data Science Physics job openings in California as of July 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 100% In-person job distribution, with an average salary of $90,571 per year, or $43.5 per hour.
Technical Director - Data Science (Discovery)

Technical Director - Data Science (Discovery)

Roblox

San Mateo, CA โ€ข Hybrid

Other

Posted 22 days ago


Job description

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers.

WHY DISCOVERY EXPERIENCES?

We're seeking senior data scientists with expertise in machine learning to join our Discovery Experience team. As IC leaders (individual contributors with a large span of influence), you'll drive strategic decisions for user growth and product innovation, leveraging all data science toolkits (analytics, experimentation, forecasting, and ML solutions) to improve end-to-end consumer journeys on Roblox. The roles will primarily focus on Discovery Experiences. Discovery surfaces (i.e. home, search, matchmaking, notifications) are critical to fostering engagement and long-term relationships with our platform. The complex network of our two-sided marketplace, combined with the ever-evolving metaverse, presents exciting challenges.

This role will report directly into the Senior Director of Data Science (Consumer) and will be based at our headquarters in San Mateo, CA (hybrid, onsite days Tues-Thurs).

You Will:
  • Develop foundational solutions to scale the hypothesis generation process across key user engagement touchpoints.
  • Contribute directly to the development of ML solutions that power our discovery canvases alongside our sister engineering teams.
  • Partner closely with Product and engineering leaders to inform, drive and accelerate innovations in discovery experiences via Insights, frameworks, causal inference solutions and machine learning prototypes.
  • Leverage advanced causal inference methodologies to measure the effectiveness of various initiatives, ranging from Roblox events to social features susceptible to network effects.
  • Conduct exploratory analysis to identify and advise XFN partners on opportunities for strategic investments.
  • Design and implement experiments for new features and communicate results succinctly to non-technical audiences.
You Have:
  • Advanced Degree and/or PhD in Statistics, Computer Science, Physics, Applied Math, Economics, or other related quantitative fields
  • 10+ years of industry experience in data science, economics, analytics, or machine learning engineering
  • 7+ years of experience using scripting languages (Python, R), and big data query/processing languages and tools such as SQL, Hive, Spark, and Airflow
  • Knowledge of ML and Deep Learning either via formal training or industry experience
  • Ability to apply creative first-principles reasoning to solve ambiguous problems
  • Experience developing large-scale recommendation systems as well as experience with content platforms, specifically user-generated content