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Mid Level Bayesian Statistics Jobs (NOW HIRING)

Huntington Ingalls Industries

$100K - $130K/yr

The ideal candidate has demonstrated experience in topics such as Bayesian inference, non ... Bachelor's degree in engineering, statistics, applied math, operations research, or similar * 5 ...

Thermo Fisher Scientific

Lead Statistician HEOR

MD · Remote

Provide guidance and advice as needed for junior and mid-level staff on projects requiring use of ... PhD in Biostatistics/Statistics or related field with 4+ years of experience, MSc in Biostatistics ...

PrizePicks

Lead Quantitative UX Researcher

Atlanta, GA · Remote

$150K - $185K/yr

Actively mentor junior and mid-level researchers, advocating for evidence-based research rigor ... Bayesian statistics) on large, unstructured datasets, alongside the ability to educate non-experts ...

ICR, Inc.

Data Scientist - Aurora, CO

Aurora, CO · On-site

$78K - $236K/yr

High level of self-initiative and self-motivation with the ability to work under minimal ... Bayesian Statistics. * Proficient C/C++. * Big Data technologies such as Hadoop MapReduce, HDFS ...

HYUNDAI-POSCO Louisiana Steel LLC

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Environmental Engineering - Mid Level

Baton Rouge, LA · On-site

This role is suited for mid-level candidates and professionals with 5 - 10 years of experience ... statistical processing skills. Preferred Education · Certified Environmental Manager (CEM ...

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All JobsMid Level Bayesian Statistics Jobs

Mid Level Bayesian Statistics information

What can you do with Bayesian statistics?

A mid-level Bayesian statistics professional can apply Bayesian methods to model uncertainty, update probabilities with new data, and improve decision-making processes across various fields such as healthcare, finance, and technology. Proficiency in statistical software like R or Python and understanding of probabilistic programming are essential for implementing these techniques effectively.

Is Bayesian statistics difficult?

Bayesian statistics as a mid-level role involves understanding probability models, prior and posterior distributions, and using tools like R or Python for analysis. While it requires a solid grasp of statistical concepts and programming skills, the difficulty depends on prior experience with mathematics and data analysis. Consistent practice and formal training can help develop proficiency in this specialized area.

What job should I do if I like statistics?

A mid-level Bayesian statistician typically works in data analysis, research, or modeling roles across industries such as healthcare, finance, or technology. These roles involve applying statistical methods, programming skills in languages like R or Python, and understanding Bayesian inference to solve complex problems. Certification or advanced degrees in statistics or related fields can enhance job prospects.

What is the difference between Mid Level Bayesian Statistics vs Data Scientist?

AspectMid Level Bayesian StatisticsData Scientist
Required CredentialsMaster's or PhD in Statistics, Mathematics, or related fieldBachelor's or higher in Data Science, Computer Science, or related field
Work EnvironmentResearch-focused, analytical, often in finance, healthcare, or academiaCross-functional teams, data analysis, machine learning, business insights
Industry UsageStatistical modeling, probabilistic analysis, research projectsData analysis, predictive modeling, data visualization

Mid Level Bayesian Statistics specialists focus on advanced probabilistic modeling and statistical inference, often in research or specialized industries. Data Scientists have a broader scope, combining statistical analysis with programming and machine learning to solve business problems. While both roles require strong analytical skills, Bayesian statisticians typically emphasize probabilistic models, whereas Data Scientists integrate multiple techniques for data-driven decision-making.

What type of statistician makes the most money?

Senior-level statisticians, such as data science managers or quantitative research directors, tend to earn the highest salaries. Specializations in machine learning, Bayesian methods, or roles in finance and technology often command higher compensation, especially with advanced skills and relevant certifications.
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Mid Level Bayesian Statistics jobs near you
Infographic showing various Mid Level Bayesian Statistics job openings in the United States as of July 2026, with employment types broken down into 4% Locum Tenens, 53% As Needed, 2% Full Time, 26% Temporary, 14% Nights, and 1% Summer. Highlights an 67% Physical, 2% Hybrid, and 31% Remote job distribution.
Bayesian Statistics Expert - Problem Designer

Bayesian Statistics Expert - Problem Designer

Mercor

San Francisco, CA • Remote

$70 - $100/hr

Full-time

Posted 9 days ago

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Computational Bayesian Statistics and Applied Mathematics Expert
Type: Contract
Compensation: $70–$100/hour
Location: Remote
Commitment: 15–20 hours/week

Role Responsibilities

  • Design challenging computational problems to test AI capabilities in solving scientific and engineering tasks.
  • Develop problems requiring the use of specialized scientific software for simulations and experiment design.
  • Refine problems through iterative testing against state-of-the-art AI models to achieve target difficulty.
  • Collaborate on creating tasks that require strategic thinking and efficient information extraction.
  • Work independently to enhance problem designs based on feedback and model performance.

Qualifications

Must-Have

  • Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
  • Proven proficiency with at least one scientific software library (PyMC, FEniCS, etc.).
  • Strong Python skills for writing problem setups and solution validators.
  • Ability to work independently and refine problem designs.
  • Comfortable in a Linux/terminal environment with remote compute sandboxes.
  • Available for at least 15–20 hours/week.

Preferred

  • Experience across multiple domains or tools.
  • Familiarity with benchmark or evaluation design.
  • Background in scientific teaching or exam/problem-set design.
  • Experience with computational reproducibility and containerized environments.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.