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Bayesian Modeling Jobs (NOW HIRING)

The Weather Channel

Senior Data Scientist

Madison, WI · On-site

As a consequence you will apply and/or learn a wide variety of statistical techniques including time series analysis, high dimensional clustering, machine learning, data mining and Bayesian modeling.

Bayesian Health

Director of AI/ML

Lead Bayesian Health's AI/ML organization with a hands-on, scrappy approach: setting technical vision, rolling up your sleeves on critical modeling work, and building a world-class team that ships ...

ChromoLogic

Senior Scientist, Bioinformatics

Monrovia, CA · On-site

$90K - $120K/yr

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

ChromoLogic

Senior Scientist, Bioinformatics

Monrovia, CA · On-site

$90K - $120K/yr

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

Airbnb

Senior Data Scientist, Trust (Inference)

Modeling : Build and iterate on statistical and Bayesian models that quantify risk, estimate treatment effects, and surface measurement gaps; provide causal interpretation of signals surfaced by ML ...

Opendoor

Applied Scientist- Pricing

Seattle, WA · On-site

... Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization • Comfort working with messy, high-dimensional real-world data and translating ambiguous ...

Redhat

Data Scientist

Raleigh, NC · On-site +1

Design, implement, and optimize predictive and statistical models using Gradient Boosting frameworks (XGBoost, LightGBM, CatBoost) and Bayesian modeling (PyMC), applying feature selection and high ...

Innovate!, Inc.

Senior Fisheries Biometrician

Seattle, WA · On-site

$120K - $165K/yr

Experience with Stan and JAGS for Bayesian modeling and posterior inference. * Strong computational skills manipulating large environmental datasets in Linux or other command-line environments ...

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How much do bayesian modeling jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for bayesian modeling in the United States is $58.71, according to ZipRecruiter salary data. Most workers in this role earn between $52.64 and $68.27 per hour, depending on experience, location, and employer.

What is Bayesian modeling?

Bayesian modeling is a statistical approach that uses Bayes' Theorem to update the probability of a hypothesis as more data becomes available. It incorporates prior beliefs or knowledge, combines them with observed data, and produces a posterior probability distribution to guide inference and decision-making. This approach is widely used in various fields such as machine learning, data science, and scientific research for tasks like parameter estimation, prediction, and model selection.

How does a Bayesian modeling specialist typically collaborate with cross-functional teams in a workplace setting?

Bayesian Modeling specialists often work closely with data scientists, software engineers, and domain experts to integrate probabilistic models into larger analytical or production systems. They are involved in translating complex statistical concepts into actionable insights and recommendations tailored to business needs. Effective communication is key, as they must present findings to both technical and non-technical stakeholders, ensuring that model assumptions and results are clearly understood. Collaboration may also include contributing to code reviews, sharing best practices for model validation, and mentoring colleagues on Bayesian methodologies.

What are the key skills and qualifications needed to thrive as a Bayesian modeler, and why are they important?

To thrive as a Bayesian Modeler, you need a solid background in statistics, probability theory, and mathematical modeling, often supported by an advanced degree in statistics, mathematics, or a related field. Proficiency with programming languages such as R, Python, or Stan, and experience with statistical software and Bayesian inference tools are essential. Strong analytical thinking, attention to detail, and effective communication skills help in interpreting results and collaborating with multidisciplinary teams. These skills ensure accurate model development, reliable data-driven insights, and clear communication of complex findings to stakeholders.

What is the difference between Bayesian Modeling vs Data Scientist?

AspectBayesian ModelingData Scientist
Required CredentialsStatistics, Mathematics, Data AnalysisStatistics, Computer Science, Data Analysis
Work EnvironmentResearch-focused, statistical modelingCross-functional, data analysis, visualization
Industry UsageResearch, academia, specialized analyticsBusiness, tech, finance, healthcare
Common Search/ComparisonYesYes

Bayesian Modeling and Data Scientists often overlap in skills like statistics and data analysis. Bayesian Modeling specializes in probabilistic models and statistical inference, while Data Scientists have broader roles including data cleaning, visualization, and machine learning. Both roles are essential in data-driven industries, but Bayesian Modeling is more focused on advanced statistical techniques.

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Bayesian Modeling jobs near you
Infographic showing various Bayesian Modeling job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $122,123 per year, or $58.7 per hour.

2027 Summer Intern, MS/PhD, Data Science - Commercialization Testing

San Francisco, CA • On-site

Waymo
Internet and IT • 1 - 5K employees
Learn more about Waymoexternal

$19.75 - $25.50/hr

Temporary, Internship

Posted 11 days ago

Job description

Waymo's Systems Engineering team works together to blend software and hardware systems in groundbreaking new ways. We set the high performance standards that ensure our vehicles run smoothly and keep passengers safe, then design and perform the tests that validate that performance. We're looking for talented teammates who'll help us maintain strong teamwork and are passionate about driving results.

Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!

You will:

  • Develop, implement, and refine Bayesian forecasting models to interpret small-sample test results.
  • Build and optimize predictive analytics models to monitor fleet operations and analyze vehicle behavior.
  • Collaborate with Test Engineers to design experimental procedures on closed courses and simulation environments.
  • Extract, process, and analyze large-scale, high-dimensional datasets from vehicle logs and depot operations using Python and SQL.
  • Partner with Systems Engineering, Software Engineering, and Product teams to determine key performance characteristics for model coverage.

You have:

  • Enrolled in a graduate program (Master's or PhD) in Data Science, Statistics, Operations Research, Civil Engineering (with a focus on traffic/mobility analytics), or a highly quantitative field.
  • Strong foundation in predictive analytics, Bayesian modeling, and statistical inference.
  • Proficiency in writing production-quality Python.
  • Strong SQL skills with experience querying and synthesizing data from large-scale databases.
  • Strong communication skills to present complex quantitative results and statistical limitations clearly to non-technical stakeholders.

We prefer:

  • Academic coursework or research experience in traffic flow theory, intelligent transportation systems, fleet routing, or urban mobility.
  • Familiarity with autonomous vehicle technology, simulation-based testing (SIL/HIL), or systems engineering principles.
  • Experience with survival analysis, probability modeling, or extreme value theory applied to safety-critical systems.
  • Comfort navigating highly ambiguous, unstructured problems in a fast-paced R&D environment.

Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in.

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