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Bayesian Statistics Jobs in California (NOW HIRING)

Swish Analytics

Tennis Data Scientist

San Francisco, CA

$135K - $190K/yr

Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods * 5+ years of demonstrated experience developing and delivering ...

Swish Analytics

NFL Data Scientist

San Francisco, CA

$140K/yr

Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods * 5+ years of demonstrated experience developing and delivering ...

Tubi

Data Scientist, Growth Analytics

Los Angeles, CA · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Evaluate and implement advanced statistical techniques - including Bayesian modeling, causal inference, uplift modeling, and media mix modeling - to improve marketing measurement and optimization.

L3HHCM20

$127K - $236K/yr

  • Medical

  • Retirement

  • PTO

... statistics expertise for various engineering, operations, and business applications. The role ... Familiarity with machine learning, Artificial Intelligence, and Bayesian methods * ASQ Certified ...

Handshake

Senior UX Researcher

San Francisco, CA · On-site

$175K - $220K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Bayesian statistics We Offer Handshake delivers benefits that help you feel supported and thrive at work and in life. The below benefits are for full-time US employees. 🎯 Ownership: Equity in a ...

L3Harris Technologies

Lead, Statistician

Canoga Park, CA

$127K - $236K/yr

  • Medical

  • Retirement

  • PTO

Graduate Degree in Engineering, Mathematics, or Statistics and a minimum of 7 years of prior ... Familiarity with machine learning, Artificial Intelligence, and Bayesian methods * ASQ Certified ...

Meta

Competitive Intelligence Lead

Burlingame, CA

$177K/yr

Proven experience with statistical analysis including causal inference (e.g., randomized control trials, quasi-experimentation such as synthetic control, diff-in-diff, meta-analyses), and/or bayesian ...

Meta

Competitive Intelligence Lead

Menlo Park, CA

$177K/yr

Proven experience with statistical analysis including causal inference (e.g., randomized control trials, quasi-experimentation such as synthetic control, diff-in-diff, meta-analyses), and/or bayesian ...

Meta

Competitive Intelligence Lead

San Francisco, CA

$177K/yr

Proven experience with statistical analysis including causal inference (e.g., randomized control trials, quasi-experimentation such as synthetic control, diff-in-diff, meta-analyses), and/or bayesian ...

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How much do bayesian statistics jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for bayesian statistics in California is $14.96, according to ZipRecruiter salary data. Most workers in this role earn between $14.95 and $14.95 per hour, depending on experience, location, and employer.

What does a typical day look like for someone working in Bayesian statistics?

A typical day for a professional specializing in Bayesian Statistics often involves designing and running statistical models, analyzing datasets using Bayesian methods, and programming in tools like R or Python. You may collaborate with data scientists, researchers, and subject matter experts to define problems and interpret statistical results. Responsibilities can also include presenting findings to non-technical stakeholders, developing new modeling techniques, and staying updated with advances in Bayesian methodology. The role offers a dynamic mix of technical analysis, problem-solving, and teamwork, making each day intellectually engaging.

What is Bayesian statistics?

A Bayesian Statistics job involves using Bayesian methods to analyze data, update probabilities, and make inferences based on prior knowledge. Professionals in this field apply Bayesian techniques in areas like machine learning, finance, healthcare, and scientific research. They typically work with probabilistic models, statistical software, and programming languages such as Python or R. These roles require strong mathematical skills and are often found in academia, industry, and government research.

What is a Bayesian statistician?

A Bayesian statistician is a professional who applies Bayesian methods to analyze data, update probabilities, and make inferences. They often use statistical software and require strong mathematical skills to develop models that incorporate prior knowledge and evidence.

What are the key skills and qualifications needed to thrive in the Bayesian statistics position, and why are they important?

To thrive in Bayesian Statistics, you need a deep understanding of probability theory, statistical modeling, and strong programming skills, usually supported by an advanced degree in statistics, mathematics, or a related field. Familiarity with technical tools like R, Python, Stan, and software for Bayesian inference, as well as relevant certifications, is often required. Analytical thinking, attention to detail, and the ability to clearly communicate complex concepts are essential soft skills. These skills and qualities ensure accurate and interpretable statistical analyses, effective collaboration with cross-functional teams, and reliable data-driven decision making.

What can you do with Bayesian statistics?

A professional in Bayesian statistics applies probabilistic models to analyze data, make predictions, and update beliefs based on new information. This skill is used in fields like data science, machine learning, and research to improve decision-making and model accuracy, often utilizing tools such as R or Python. Bayesian methods are valuable for tasks involving uncertainty quantification and sequential data analysis.

What jobs use Bayesian statistics?

Bayesian statistics is used in a variety of roles including data scientist, quantitative analyst, biostatistician, machine learning engineer, and research scientist. These jobs often require skills in statistical modeling, programming languages like R or Python, and experience with probabilistic methods to analyze data and inform decision-making.

What are the most commonly searched types of Bayesian Statistics jobs in California?

The most popular types of Bayesian Statistics jobs in California are:

What are popular job titles related to Bayesian Statistics jobs in California?

For Bayesian Statistics jobs in California, the most frequently searched job titles are:

What job categories do people searching Bayesian Statistics jobs in California look for?

The top searched job categories for Bayesian Statistics jobs in California are:

Bayesian Statistics jobs near you
Infographic showing various Bayesian Statistics job openings in California as of August 2026, with employment types broken down into 78% Full Time, 18% Part Time, 2% Temporary, and 2% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $31,120 per year, or $15 per hour.

Soccer Data Scientist

Swish Analytics

San Francisco, CA

$130K/yr

Full-time

Re-posted 19 days ago

Job description

Company Description

Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.

Job Description

Swish Analytics is looking for a Soccer Data Scientists to join our ever-growing team! Data Science is at the core of our business, so this team has true ownership and impact over developing core components of Swish's data products. This position is remote from the USA.

Duties:

  • Ideate, develop and improve machine learning and statistical models that drive Swish’s core algorithms for producing state-of-the-art sports betting products.

  • Develop contextualized feature sets using sports specific domain knowledge.

  • Contribute to all stages of model development, from creating proof-of-concepts and beta testing, to partnering with data engineering and product teams to deploy new models.

  • Strive to constantly improve model performance using insights from rigorous offline and online experimentation.

  • Analyze results and outputs to assess model performance and identify model weaknesses for directing development efforts.

  • Adhere to software engineering best practices and contribute to shared code repositories.

  • Document modeling work and present to stakeholders and other technical and non-technical partners.

Requirements:

  • Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area

  • Demonstrated experience developing models at production scale for Soccer, or sports betting for 2+ years

  • Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods

  • 5+ years of demonstrated experience developing and delivering effective machine learning and/or statistical models to serve business needs in sports or sports betting

  • Experience with relational SQL & Python

  • Experience with source control tools such as GitHub and related CI/CD processes

  • Experience working in AWS environments etc

  • Proven track record of strong leadership skills. Has shown ability to partner with teams in solving complex problems by taking a broad perspective to identify innovative solutions

  • Excellent communication skills to both technical and non-technical audiences

Base Salary: Starting at $130,000

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.