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Probabilistic Programming Bayesian Jobs (NOW HIRING)

Numerator

Sr. Data Scientist II

You'll partner with Product, Data, and Engineering teams to translate customer needs into data ... Lead the design and delivery of complex Bayesian and probabilistic modeling pipelines, from ...

New

General Atomics

Data Scientist III

Charlottesville, VA · On-site

$98K - $171K/yr

Job Summary Are you a statistician who wants to see your Bayesian models protect national security ... Experience with probabilistic programming frameworks * Dissertation work involving real-world ...

General Atomics

Data Scientist III

Charlottesville, VA · On-site

Job Summary Are you a statistician who wants to see your Bayesian models protect national security ... Experience with probabilistic programming frameworks * Dissertation work involving real-world ...

Avathon

Senior AI Scientist - Planning

Pleasanton, CA

$160K - $240K/yr

Familiarity with probabilistic programming or Bayesian methods for demand sensing * Experience with cloud ML infrastructure (AWS SageMaker, GCP Vertex, or equivalent) * Domain experience in energy ...

Avathon

Senior AI Scientist - Planning

Pleasanton, CA · On-site

Familiarity with probabilistic programming or Bayesian methods for demand sensing * Experience with cloud ML infrastructure (AWS SageMaker, GCP Vertex, or equivalent) * Domain experience in energy ...

Numerator

You'll partner with Product, Data, and Engineering teams to translate customer needs into data ... Lead the design and delivery of complex Bayesian and probabilistic modeling pipelines, from ...

Numerator

You'll partner with Product, Data, and Engineering teams to translate customer needs into data ... Lead the design and delivery of complex Bayesian and probabilistic modeling pipelines, from ...

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Probabilistic Programming Bayesian information

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$153.5K

$280.1K

$344K

How much do probabilistic programming bayesian jobs pay per year?

As of Jul 18, 2026, the average yearly pay for probabilistic programming bayesian in the United States is $280,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $260,500.00 and $322,500.00 per year, depending on experience, location, and employer.

What are the typical challenges faced by professionals working in Probabilistic Programming with a Bayesian focus, and how can they be addressed?

Professionals working in Probabilistic Programming with a Bayesian focus often encounter challenges related to model complexity, computational efficiency, and communicating results to non-technical stakeholders. Building accurate Bayesian models requires careful selection of priors and an understanding of underlying data distributions, which can be demanding without robust domain expertise. Additionally, computational demands can be high, especially for large datasets or complex hierarchical models, making efficient sampling and approximation methods essential. Collaborating closely with domain experts and leveraging modern probabilistic programming frameworks can help address these challenges and ensure practical, interpretable results.

What is probabilistic programming in the context of Bayesian statistics?

Probabilistic programming in the context of Bayesian statistics refers to writing computer programs that use probability distributions and Bayesian inference to model uncertainty and learn from data. These programs allow users to define complex probabilistic models using code, making it easier to specify, fit, and analyze Bayesian models. Probabilistic programming languages, such as Stan, PyMC, or Edward, provide tools to automate inference, enabling practitioners to focus on modeling rather than mathematical derivations. This approach is widely used in fields like machine learning, data science, and scientific research to handle uncertainty and make predictions.

What is the difference between Probabilistic Programming Bayesian vs Data Scientist?

AspectProbabilistic Programming BayesianData Scientist
Required credentialsBackground in statistics, probability, programmingStatistics, computer science, or related degree
Work environmentResearch, modeling, algorithm developmentData analysis, visualization, business insights
Industry usageAI, machine learning, research projectsBusiness, finance, tech, healthcare

Probabilistic Programming Bayesian focuses on developing models using Bayesian methods and probabilistic programming languages, often in research or AI development. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles require statistical knowledge, Bayesian programmers specialize in probabilistic modeling, whereas Data Scientists apply a broader set of data analysis techniques.

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

To thrive as a Probabilistic Programming Bayesian specialist, you need a strong background in statistics, probability theory, and Bayesian inference, often supported by a degree in mathematics, statistics, computer science, or a related field. Expertise with probabilistic programming languages (such as Stan, PyMC, or TensorFlow Probability) and familiarity with statistical modeling software are also essential. Analytical thinking, problem-solving, and effective communication skills help translate complex models into actionable insights and collaborate with interdisciplinary teams. These skills and qualities are crucial for developing robust, interpretable models that inform decision-making in research and industry applications.
More about Probabilistic Programming Bayesian jobs
What cities are hiring for Probabilistic Programming Bayesian jobs? Cities with the most Probabilistic Programming Bayesian job openings:
What states have the most Probabilistic Programming Bayesian jobs? States with the most job openings for Probabilistic Programming Bayesian jobs include:
What job categories do people searching Probabilistic Programming Bayesian jobs look for? The top searched job categories for Probabilistic Programming Bayesian jobs are:
Probabilistic Programming Bayesian jobs near you
Infographic showing various Probabilistic Programming Bayesian job openings in the United States as of July 2026, with employment types broken down into 16% As Needed, 19% Full Time, 5% Part Time, 32% Temporary, 25% Nights, and 3% Summer. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution, with an average salary of $280,147 per year, or $134.7 per hour.
Sr. Data Scientist II

Sr. Data Scientist II

Numerator

Remote

Full-time

Posted yesterday

New

Job description

Numerator is seeking a Sr. Data Scientist II (Bayesian Modeling) to help build, enhance, and scale data science services across our rapidly evolving data platform. You'll work end-to-end on initiatives that turn massive proprietary datasets into impactful, production-grade solutions.
This is a highly autonomous, product-focused role. You'll partner with Product, Data, and Engineering teams to translate customer needs into data-driven products, analytics methodologies, and new offerings that drive measurable business impact.
How You'll Spend Your Time:
  • Lead the design and delivery of complex Bayesian and probabilistic modeling pipelines, from methodology through production
  • Set technical direction on hard modeling problems and make the key methodological calls, with a high degree of autonomy
  • Work closely with Product, GTM, Data, and Engineering to turn models into reliable, production-grade solutions the business can depend on
  • Help the whole team get better - mentor other data scientists, share your approach openly, and raise the bar for how the group reasons about uncertainty and Bayesian methods
  • Communicate methods, results, and tradeoffs clearly to both technical and non-technical audiences
Skills & Requirements
  • Strong foundation in Bayesian inference and probabilistic modeling - e.g. hierarchical / multilevel models, state-space and time-series models, graphical models, MCMC/HMC, variational and other approximate inference
  • Experience applying these methods to real, messy, production data - not only research or coursework
  • Comfort reasoning about uncertainty, calibration, and model validation
  • Facility with large or structured datasets and the computational side of inference at scale
  • Strong Python, and fluency in a modern probabilistic-programming and numerical-computing stack - NumPyro, PyMC, Stan, JAX, dynamax, or similar. We hire on the ideas, not on exact tooling
  • Track record of shipping statistical models into production
  • BS or PhD in Statistics, Math, Economics, Physics, CS, or a related quantitative field
  • 8+ years of industry experience as a data scientist (or equivalent role/work) with a BS in the above-mentioned areas, or 5+ years of industry experience with a PhD in a quantitative field
  • Clear communication with both technical and non-technical audiences

Nice to Haves:
  • Diagnosing and debugging large Bayesian models - convergence and divergence issues, pinning down which part of a big model is misbehaving, and knowing which inference method to reach for
  • Weighting a non-representative survey or panel sample up to a known population, and a feel for where those adjustments break down
  • Hierarchical models spanning multiple crossed or overlapping groupings - relationships that bridge hierarchies, not just a single nested tree
  • Experience with graph or network models, or modeling relational / graph-structured data
  • Measurement-error modeling, or reconciling multiple imperfect data sources
  • CPG / FMCG / retail experience, or work with user-level purchase or panel data

#LI-Remote
There is strength in numbers - We are the Numerati
Numerator is 2,000 employees strong. We have the confidence to be real and embrace what makes each Numerati unique. Our diverse experiences, ideas and backgrounds fuel our innovation.
Being part of the Numerati means that we'll take care of you! From our Recharge Days, maximum flexibility policy, wellness resources for employees and their families, development opportunities and much more - we're always finding ways to better support, celebrate and accelerate our team.

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