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Data Science R Jobs in California (NOW HIRING)

Waymo

Data Scientist

San Diego, CA

Autonomous driving presents a new paradigm in data science: in addition to leveraging data ... Demonstrated knowledge of Python/SQL/R data analysis libraries and packages We prefer: * PhD in a ...

Heluna Health

Data Scientist Supervisor

Alhambra, CA · On-site

$9.8K - $13K/mo

Quality Assurance & Best Practices - Establish and enforce best practices in data science ... Advanced programming skills in Python, R, and SQL for model development and data processing.

Heluna Health

Data Scientist Supervisor

Alhambra, CA

$9.8K - $13K/mo

Quality Assurance & Best Practices - Establish and enforce best practices in data science ... Advanced programming skills in Python, R, and SQL for model development and data processing.

Compunnel

Data Scientist

San Francisco, CA · On-site

... Data Science and modeling. - Train the Users by providing models and materials to be used for ... R, Stata) and production ML pipelines. - Review and provide feedback on AI/ML architectural ...

TikTok

Data Science Manager - TikTok Ads

San Jose, CA · On-site

$254K - $422K/yr

R, Python, MATLAB) and database languages (e.g. SQL) 5. Experience building data science models (Regression, Decision Trees, K-Means, etc.) 6. Experience with large data sets and analytical tools, e ...

Stefanini Group

Data Scientist

San Francisco, CA · On-site

Bridge the gap between econometric models (R, Stata) and production ML pipelines * Review and ... Help other Support Team members advance their knowledge of Data Science and modeling Qualifications:

Stefanini Group

Data Scientist

San Francisco, CA · On-site

Bridge the gap between econometric models (R, Stata) and production ML pipelines * Review and ... Help other Support Team members advance their knowledge of Data Science and modeling Qualifications:

Stefanini Group

Data Scientist

San Francisco, CA · On-site

Bridge the gap between econometric models (R, Stata) and production ML pipelines * Review and ... Help other Support Team members advance their knowledge of Data Science and modeling Qualifications:

Ignite Digital

Mid Data Scientist

San Diego, CA

Stay current with emerging data science methodologies, tools, and industry best practices * Ensure ... Proficiency in Python or R for statistical modeling and machine learning * Strong knowledge of SQL ...

Asana

Data Scientist

San Francisco, CA · On-site

$171K - $230K/yr

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven ... Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data ...

Asana

Data Scientist

San Francisco, CA · On-site +1

$171K - $230K/yr

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven ... Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data ...

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Data Science R information

What is a Data Science R job?

A Data Science R job involves using the R programming language for data analysis, statistical modeling, and machine learning. Professionals in this role work with large datasets, clean and preprocess data, apply predictive modeling techniques, and visualize insights. They often use libraries like ggplot2, dplyr, and caret to manipulate data and build models. This role is common in industries such as finance, healthcare, and marketing, where data-driven decision-making is essential. Strong statistical knowledge, programming skills, and domain expertise are key to success in this position.

What are the typical daily tasks for a Data Science R professional in most organizations?

In most organizations, Data Science R professionals spend their days gathering and cleaning data, performing exploratory data analysis with R, building and evaluating predictive models, and generating data visualizations to communicate results. They often meet with cross-functional teams to understand business needs, translate them into data projects, and present key findings. Additionally, they may write reproducible R scripts, maintain data pipelines, and document their methodologies. Collaboration, experimentation, and clear communication are integral parts of the role, enabling solutions that directly impact business outcomes.

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

To thrive as a Data Science R professional, you need solid expertise in statistics, machine learning, and programming in R, often supported by a degree in data science, statistics, or a related field. Experience with R-based data analysis libraries, visualization tools like ggplot2, and familiarity with databases or cloud platforms is typically expected; certifications in data science or R programming can be advantageous. Strong problem-solving abilities, attention to detail, and effective communication with stakeholders help distinguish top performers in this role. These skills are essential for delivering actionable insights from complex datasets and driving data-informed decision-making within organizations.

What are the most commonly searched types of Data Science R jobs in California? The most popular types of Data Science R jobs in California are:
What are popular job titles related to Data Science R jobs in California? For Data Science R jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Science R jobs in California look for? The top searched job categories for Data Science R jobs in California are:
What cities in California are hiring for Data Science R jobs? Cities in California with the most Data Science R job openings:
Data Science R jobs near you
Infographic showing various Data Science R 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.
Data Scientist

Data Scientist

Waymo

San Diego, CA

Other

Re-posted 11 days ago

Job description

Rigorous performance evaluation of the Waymo Driver is a critical part of scaling our ride hailing service and achieving Waymo's audacious goals. Waymo data scientists work hand-in-hand with engineering teams at each stage of the software development cycle, employing statistical models and developing metrics and measurement frameworks to ensure that the Waymo Driver meets our strict standards for safety, compliance, and driving and service quality. Autonomous driving presents a new paradigm in data science: in addition to leveraging data collected on-road, we generate our own data using state-of-the-art simulation technology-resulting in denser signals and challenging new problems in estimation and experimental design.

In this hybrid role you will report to a Data Science Manager.

You will:

  • Develop evaluation frameworks for autonomous vehicle performance, for large-scale ML models, and for the quality of simulation.
  • Develop new metrics, interpret trends, and investigate anomalies in data from simulation and on-road driving.
  • Develop novel statistical methods to handle unique aspects of AV data; e.g. rate estimation with rare events, combining real and synthetic data, etc.
  • Frame and solve ambiguous problems, derive data-driven conclusions, and communicate findings to senior stakeholders.
  • Collaborate with Product and Engineering partners developing the Waymo Driver and Waymo's simulation software; facilitate deployment readiness decisions for both products.

You have:

  • Degree in a quantitative field (e.g. Statistics, Mathematics, Physics)
  • 3+ years of industry experience solving data science problems or a PhD in a quantitative field
  • Expertise using advanced statistical methods in an applied setting; familiarity with ML systems/models
  • Demonstrated knowledge of Python/SQL/R data analysis libraries and packages

We prefer:

  • PhD in a quantitative field
  • Experience solving problems related to Autonomous Driving or Ride Hailing
  • Experience in adjacent relevant areas like Advanced Machine Learning (Deep Learning and Diffusion models), Traffic Modeling, Safety Evaluation or Prediction

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