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Bayesian Statistics Jobs in California (NOW HIRING)

Apply advanced machine learning, Bayesian statistics, and predictive modeling techniques to identify biologically meaningful patterns and biomarkers * Design and execute end-to-end analytical ...

... Bayesian statistics and multivariate analysis • Experience with version control systems (e.g., GitHub) • Experience building responsive web applications with Angular / JavaScript (Typescript ...

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

Explainable AI Engineer

Palo Alto, CA · Remote

$122K - $165K/yr

Bayesian statistics * Monte Carlo analysis * Mathematical optimization * Decision and Control * Experience with MATLAB * Model-based development / simulation-based verification * Solid experience ...

Tennis Data Scientist

San Francisco, CA · On-site +1

$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 ...

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Bayesian Statistics information

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How much do bayesian statistics jobs pay per hour?

As of Sep 13, 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 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 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 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 uncertainty. Proficiency in statistical software such as R or Python is often required.

What is a Bayesian statistician?

A Bayesian statistician is a professional who applies Bayesian methods to analyze data, update probabilities, and make statistical inferences. They often use tools like statistical software and require strong knowledge of probability theory and modeling techniques to interpret data within a Bayesian framework.

What jobs use Bayesian statistics?

Jobs that use Bayesian statistics include data scientists, statisticians, machine learning engineers, and quantitative analysts. These roles often involve developing probabilistic models, analyzing data, and making predictions using Bayesian methods and tools like R or Python. Strong analytical skills and knowledge of statistical software are typically required.

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:

Infographic showing various Bayesian Statistics job openings in California as of September 2026, with employment types broken down into 2% Internship, 78% Full Time, 18% Part Time, and 2% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $31,120 per year, or $15 per hour.

Senior Research Data Scientist, Meridian AI

Mountain View, CA • On-site

Google Inc.
Software Development • 10K+ employees

Other

Posted 24 days ago


Google rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz


Job description

Senior Research Data Scientist, Meridian AI

Share Senior Research Data Scientist, Meridian AI


Google New York, NY, USA ; Mountain View, CA, USA


Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.


Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Mountain View, CA, USA.



  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.

  • 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.

  • Experience with econometrics, machine learning and Bayesian statistics.


Preferred qualifications:

  • 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.


About the job

As a part of the Meridian AI team, you will focus on revolutionizing Marketing Mix Modeling (MMM) by building an autonomous, agent-based AI product that automates the traditionally complex, high-friction model-building life-cycle.


Your mission is to democratize access to advanced media effectiveness measurement for Google's advertisers and agencies while also drastically improving modeling productivity and quality.


In this role, you will have the unique opportunity to bridge the gap between traditional data science and the next-generation AI. You will combine your deep econometric and statistical expertise with cutting-edge agentic technology to build Subject Matter Expert (SME) agents from the ground up, effectively encoding human analytical intuition into an autonomous system that scales expert-level measurement globally.


You will bring scientific and statistical methods to bear on the challenges of advertising product creation, development and improvement with a deep, data-driven appreciation for the behaviors of the end user and the ecosystem. As a Data Scientist on the Meridian AI team, you will shape the strategic technical direction of Google’s next-generation marketing analytics. In this pioneering role, you will act as the crucial bridge between classical data science and frontier AI. Your primary focus will be leading the research and development of advanced Marketing Mix Modeling (MMM) methodologies and embedding rigorous Bayesian statistics, causal inference, and machine learning into autonomous AI agents. By encoding human econometric reasoning into Large Language Model (LLM) driven workflows, you will build intelligent systems capable of solving highly complex measurement challenges from the ground up, ensuring Google remains the undisputed industry leader in automated, scalable marketing measurement.


Individual pay is determined by factors including job-related skills, experience, and relevant education or training.


US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits


Learn more about benefits at Google .



  • Lead the design and development of innovative measurement methodologies and products, setting the strategic technical direction for Meridian and AI development.

  • Serve as the core bridge between classical data science and frontier AI by embedding rigorous Bayesian statistical frameworks into autonomous AI agents, encoding econometric reasoning, heuristic logic, and human analytical intuition into LLM-driven workflows from the ground up.

  • Pioneer advanced quantitative methods by integrating cutting-edge causal inference, statistical modeling, and machine learning techniques to solve highly ambiguous and complex measurement challenges.

  • Drive the research and development of next-generation Marketing Mix Modeling (MMM) methodologies, setting the technical strategy for integrating advanced econometric models into the Meridian AI product suite, ensuring Google remains at the forefront of marketing analytics.


Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .


Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.


Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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