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Bayesian Statistics Jobs (NOW HIRING)

Think Tank, Inc.

Statistician

Seattle, WA

Knowledge and experience in Bayesian statistics and mark-recapture methods is strongly preferred. * Advanced degree in a related field - may substitute for two (MS) or four (PhD) years of experience ...

New

Exponent

Statistical Scientist (Ph.D.)

Bellevue, WA · On-site

... Bayesian statistics, machine learning, or quality control/improvement • Minimum of 2 years' experience with one or more statistical software packages (SAS and R are preferred) • Ability to work ...

MD Anderson

Postdoctoral Fellow - Biostatistics

Houston, TX · On-site +1

$64K - $76K/yr

The primary research focus will be on developing novel statistical methodologies and software for Bayesian adaptive clinical trial designs. The postdoctoral fellow will also actively participate in ...

MD Anderson

Postdoctoral Fellow - Biostatistics

Houston, TX · On-site +1

$64K - $76K/yr

The primary research focus will be on developing novel statistical methodologies and software for Bayesian adaptive clinical trial designs. The postdoctoral fellow will also actively participate in ...

Wood Plc

Environmental Statistician

Kennesaw, GA · On-site +1

Experience with Bayesian statistics a plus * Experience with censored datasets a plus * Master's degree or PhD a plus * Must pass drug test, physical, background check, and must have a satisfactory ...

MD Anderson

Postdoctoral Fellow - Biostatistics

Houston, TX · On-site +1

$64K - $76K/yr

The primary research focus will be on developing novel statistical methodologies and software for Bayesian adaptive clinical trial designs. The postdoctoral fellow will also actively participate in ...

ICR, Inc.

Data Scientist - Aurora, CO

Aurora, CO · On-site

$78K - $236K/yr

Bayesian Statistics. * Proficient C/C++. * Big Data technologies such as Hadoop MapReduce, HDFS, Apache Spark, Apache Storm, ELK Stack. * Masters Degree or PhD in Mathematics, Physics, Statistics ...

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How much do bayesian statistics jobs pay per year?

As of Jul 10, 2026, the average yearly pay for bayesian statistics in the United States is $90,119.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,500.00 and $106,500.00 per year, 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 type of statistician makes the most money?

Senior statisticians with expertise in Bayesian methods, data science, or machine learning tend to earn higher salaries, especially in industries like finance, technology, and pharmaceuticals. Advanced skills, certifications, and experience with programming tools such as R or Python can also increase earning potential.

What industries use Bayesian statistics?

Bayesian statistics is widely used across industries such as healthcare, finance, marketing, and technology for data analysis, predictive modeling, and decision-making. Professionals in these fields often utilize statistical software like R or Python and require strong analytical skills to interpret probabilistic models effectively.

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 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. Familiarity with statistical software and programming languages such as R or Python is often required.
More about Bayesian Statistics jobs
What are the most commonly searched types of Bayesian Statistics jobs? The most popular types of Bayesian Statistics jobs are:
What states have the most Bayesian Statistics jobs? States with the most job openings for Bayesian Statistics jobs include:
What job categories do people searching Bayesian Statistics jobs look for? The top searched job categories for Bayesian Statistics jobs are:
Bayesian Statistics jobs near you
Infographic showing various Bayesian Statistics job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $90,119 per year, or $43.3 per hour.
Bayesian Statistician (Data Scientist) - Aurora, CO

Bayesian Statistician (Data Scientist) - Aurora, CO

ICR, Inc.

Aurora, CO

$78K - $236K/yr

Full-time

Medical, Retirement, PTO

Re-posted 11 days ago

Job description

Bayesian Statistician (Data Scientist)
Aurora, CO
Applications will be accepted on an ongoing basis.

ICR has opportunities available for experienced and motivated Data Scientists with a Bayesian statistics background.
Essential Job Responsibilities
This Data Scientist will be expected to:
  • Work independently on complex technical tasks that require in-depth data analysis methodologies and data/information collection
  • Develop unique technical solutions for applications in the intelligence field
  • Participate as a member of a multidisciplinary team to analyze and satisfy customer requirements
  • Develop, implement, validate, document, and present findings of specialized analysis software tools and models as required
  • Effectively handle concurrent technical tasks with conflicting priorities
  • Approach difficult problems with enthusiasm and creativity
  • Have the ability to change focus when necessary
  • Travel (up to 10%)

Required Skills and Qualifications
  • Active Top Secret Security Clearance with SSBI and SCI eligibility.
  • Experience with Bayesian statistics and time series analysis
  • Masters Degree in statistics with a minimum of Two (2) years of professional experience or PhD in statistics or related field
  • Experience with computational analysis tools and developing software with at least one of the following programing language: Python (preferred), R, C++, MATLAB
  • Experience with developing and applying advanced statistical/machine learning models and algorithms for one or more of the following: classification, clustering, anomaly detection, density estimation, data mining, pattern recognition, knowledge discovery
  • Experience with extracting and processing structured/unstructured data from various sources (e.g. databases, text files, web) and preparing data for analysis
  • Collaborate with others in a multidisciplinary team environment to accomplish research goals
  • Ability to work effectively in small-team settings to solve complex problems
  • Ability and desire to obtain substantial domain knowledge in fields of application and ability to communicate effectively with subject matter experts
  • Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information to customers

Desired Qualifications
  • Experience with the intelligence community
  • Broad knowledge of statistical analysis, ML methods, and problem-solving skills
  • Experience with: spatial statistics, multivariate statistics, Gaussian Process, Random Forest, Support Vector Machine, Natural Language Processing, Neural Networks
  • Proficient with Python, Jupyter, Markdown
  • Experience working with databases such as SQL and/or ELK stack
  • Experience with creating data visualizations / dashboards
Salary Range: $78,853 - $236,579
This position offers a comprehensive benefits package that includes company equity, retirement plan, company-paid health care benefits, flexible paid time off policy, and opportunity for a raise and bonus during the year.
ICR, Inc. considers several factors when extending job offers, including but not limited to candidates’ key skills, relevant work and/or military experience, education, training certifications and work location.
ICR is proud to be an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.

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