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Bayesian Statistics Jobs in California (NOW HIRING)

Intuit

Staff AI Scientist

Mountain View, CA · On-site

$205K - $278K/yr

... Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent * 4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian ...

Amplitude

Senior Data Scientist

San Francisco, CA · On-site

As a Data Scientist, you will influence product development through advanced statistical ... modeling • Bayesian hypothesis testing • Understanding how teams run experiments • B2B ...

Intuit

Staff AI Scientist

Mountain View, CA

$205K - $278K/yr

... Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent * 4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian ...

Intuit

Staff AI Scientist

Mountain View, CA · On-site

$205K - $278K/yr

... Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent * 4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian ...

Intuit

Staff AI Scientist

Mountain View, CA · On-site

... Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent * 4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian ...

Intuit

Staff AI Scientist

Mountain View, CA · On-site

... Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent * 4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian ...

Intuit

Staff AI Scientist

Mountain View, CA

... Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent * 4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian ...

ASM Global

Manger, Modeling Insights

Los Angeles, CA · On-site

$90K - $100K/yr

This role supports oursports and entertainmentbusinesses and combines strong statistical ... Build and maintainstatistical, Bayesian, and machine learning modelsfor use cases including lead ...

InMobi

Applied Scientist III

San Mateo, CA

Statistical learning theory, optimization, probability theory, and information theory * Causal inference, decision theory, game theory * Online learning, bandits, RL, Bayesian methods * Strong ...

Federato Technologies

Data Scientist

San Francisco, CA · Remote

$160K - $200K/yr

... Statistics, and Optimization. The role will report directly to the CTO. Next to the CTO, you will ... Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization ...

Federato Technologies

Data Scientist

San Francisco, CA · On-site +1

$160K - $200K/yr

... Statistics, and Optimization. The role will report directly to the CTO. Next to the CTO, you will ... Graduate work in an optimization related field (e.g RL, Convex Optimization, Bayesian Optimization ...

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Bayesian Statistics information

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How much do bayesian statistics jobs pay per hour?

As of Jun 15, 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 a Bayesian Statistics job?

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 can develop probabilistic models to analyze data, make predictions, and update beliefs based on new information. These skills are valuable in fields like data science, machine learning, and research, often using tools such as R or Python. Bayesian methods support decision-making under uncertainty and are applicable in various industries including healthcare, finance, and technology.

Is Bayesian statistics difficult?

Bayesian statistics as a job involves understanding probability models and applying statistical software like R or Python. It can be challenging initially due to its mathematical concepts, but with practice and training, it becomes manageable for those with a background in mathematics or data analysis.
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 June 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $31,120 per year, or $15 per hour.
Staff AI Scientist

Staff AI Scientist

Intuit

Mountain View, CA • On-site

$205K - $278K/yr

Full-time

Posted 4 days ago

Intuit rating

8.4

Company rating: 8.4 out of 10

Based on 83 frontline employees who took The Breakroom Quiz

66th of 190 rated software companies

Job description

Overview

Intuit is looking for an innovative and hands-on Staff AI Scientist to join the Intuit AI team.

Come join our collaborative and creative group of AI scientists and machine learning engineers and build models that directly affect hundreds of thousands of our customers. In this role you will be building and deploying machine learning models using both analytical algorithms and deep learning approaches. 


Responsibilities

  • Practices leadership and communication skills to influence teams and to evangelize AI science across the organization
  • Collaborates with stakeholders to define success criteria and align model metrics with business goals. Works side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products
  • Leads technical work of a scrum team: initiating and designing model solutions, driving end-to-end architecture designs of the team’s work, and holding the team accountable for high quality code, git, design, costs and implementation standards
  • Performs hands-on data analysis and modeling with large data sets, including discovering data sources, getting data access, cleaning up data, and making them “model-ready”. You need to be willing and able to do your own ETL and design/build featurization. 
  • Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets.  
  • Runs A/B tests to draw conclusions on the impact of your team’s work and communicates results to peers and leaders
  • Communicates with partners to ensure successful delivery and integration of DS solutions.  
  • Proactively researches, explores, and enables new ML technologies. Keeps up with the new developments in academia and industry and considers possible extensions to solve Intuit customer problems. 
    Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

Qualifications

  • 4+ years of industry experience with AI science
  • BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent
  • 4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian, Reinforcement or Deep Learning.
  • Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization.
  • Proficient  in NLP techniques, Explainable AI, and ML frameworks. 
  • Expertise in modern advanced analytical tools and programming languages such as Python, Scala, Java and/or R.
  • Efficient in SQL, Hive, SparkSQL, etc.
  • Comfortable working in a Linux environment
  • Experience with building end-to-end reusable pipelines from data acquisition to model output delivery
  • Quick learner, adaptable, with the ability to work independently in a fast-paced environment
  • Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:  
Mountain View, CA:$205,500 - $278,000

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