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Postdoctoral In Bayesian Statistics Jobs in Seattle, WA

AIS Inc

Quantitative Analyst (COMPASS Modeling)

Seattle, WA · On-site

$100 - $140/hr

Master's degree in a related quantitative or natural science field. * Experience with Bayesian statistical methods and mark-recapture analysis. * Experience with Bayesian modeling programs Stan and ...

Binaytara

Postdoctoral Research Fellow

Bellevue, WA · On-site

Overview Binaytara seeks a motivated and intellectually rigorous Postdoctoral Research Fellow to ... in underserved populations. * Lead or contribute to data management, statistical analysis, and ...

Meta

Competitive Intelligence Lead

Seattle, WA

$177K/yr

Proven experience with statistical analysis including causal inference (e.g., randomized control trials, quasi-experimentation such as synthetic control, diff-in-diff, meta-analyses), and/or bayesian ...

Meta

Competitive Intelligence Lead

Bellevue, WA

$177K/yr

Proven experience with statistical analysis including causal inference (e.g., randomized control trials, quasi-experimentation such as synthetic control, diff-in-diff, meta-analyses), and/or bayesian ...

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Postdoctoral In Bayesian Statistics information

See Seattle, WA salary details

$28.5K

$67.2K

$95K

How much do postdoctoral in bayesian statistics jobs pay per year?

As of Aug 22, 2026, the average yearly pay for postdoctoral in bayesian statistics in Seattle, WA is $67,168.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,800.00 and $75,700.00 per year, depending on experience, location, and employer.

What is a postdoctoral position in Bayesian statistics?

A Postdoctoral position in Bayesian Statistics is a research-focused role for individuals who have recently completed their PhD in statistics, mathematics, or a related field. These positions involve conducting advanced research using Bayesian methods, which apply probability to infer statistical conclusions. Postdocs often work on developing new Bayesian models, collaborating on interdisciplinary projects, and publishing research findings. Such positions are typically temporary and designed to further prepare researchers for academic, industry, or governmental roles.

What are the key skills and qualifications needed to thrive as a postdoctoral researcher in Bayesian statistics?

To thrive as a Postdoctoral Researcher in Bayesian Statistics, you need an advanced degree (typically a PhD) in statistics or a related field, with strong expertise in Bayesian inference and probabilistic modeling. Proficiency with statistical programming languages such as R, Python, or Stan, and experience with specialized Bayesian analysis software are highly valued. Excellent problem-solving skills, collaboration, and the ability to communicate complex statistical concepts clearly are standout soft skills for this role. These skills and qualities are crucial for conducting rigorous research, publishing impactful results, and contributing effectively to scientific teams.

What are some common challenges faced by postdoctoral researchers in Bayesian statistics, and how can they be addressed?

Postdoctoral researchers in Bayesian statistics often encounter challenges such as managing complex, high-dimensional data, staying current with rapidly evolving computational methods, and balancing independent research with collaborative projects. Effective strategies include leveraging open-source statistical software, actively participating in seminars and workshops to stay updated, and establishing regular communication with interdisciplinary teams. Building a strong professional network and seeking mentorship within the department can also help in navigating research obstacles and advancing one's career.

What is the difference between Postdoctoral In Bayesian Statistics vs Postdoctoral In Data Science?

AspectPostdoctoral In Bayesian StatisticsPostdoctoral In Data Science
Required CredentialsPhD in Statistics, Mathematics, or related fieldPhD in Computer Science, Statistics, or related field
Work EnvironmentAcademic research, university labsResearch institutions, tech companies, industry labs
Employer & Industry UsageUniversities, research institutesTech firms, finance, healthcare, consulting
Common Search & Comparison IntentSpecialized research roles in Bayesian methodsBroader data analysis and machine learning roles

Postdoctoral In Bayesian Statistics focuses on advanced research in Bayesian methods within academic settings, requiring deep statistical expertise. In contrast, Postdoctoral In Data Science covers a broader range of data analysis techniques, including machine learning, often in industry environments. Both roles require a PhD but differ in application focus and work environment.

What are popular job titles related to Postdoctoral In Bayesian Statistics jobs in Seattle, WA?

For Postdoctoral In Bayesian Statistics jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Postdoctoral In Bayesian Statistics jobs in Seattle, WA look for?

The top searched job categories for Postdoctoral In Bayesian Statistics jobs in Seattle, WA are:

Postdoctoral In Bayesian Statistics jobs near you

Quantitative Analyst - COMPASS Modeling

Think Tank, Inc.

Seattle, WA

Full-time

Re-posted 14 days ago

Job description

*Position is Subject to Contract Award

POSITION DESCRIPTION:

Description of Duties:

  • Develop and advance the Comprehensive Passage (COMPASS) model for application in river systems to evaluate effects of stressors and management actions across fish life cycles, using statistical modeling, computer modeling, statistical/quantitative analysis, and other quantitative modeling techniques.
  • Construct and implement models evaluating survival and migration through the hydropower system (COMPASS model) to address West Coast Regional Office requests in support of ESA litigation and permitting.
  • Collaborate with regional managers and researchers to structure, synthesize, and manage environmental and biological data relevant to modeling needs.
  • Document and share reproducible research workflows and analytical products.
  • Write reports, contribute to journal manuscripts, and present results at regional and national meetings and conferences, as needed.
  • Assist with field collection of fish and environmental data as needed (may involve riding in vehicles and/or boats).

EDUCATION & EXPERIENCE:

Required:

  • Education: Bachelor's degree or higher from an accredited college/university with a major related to the task order and a strong quantitative background, with emphasis in statistics, mathematics, fisheries, ecology, or the natural sciences.
  • Experience: Three (3) or more years of experience related to the task order.

Desired:

  • Master's degree preferred.
  • Advanced degree in a related field - may substitute for two (MS) or four (PhD) years of experience

CERTIFICATIONS: 

Required:

  • Valid U.S. driver's license - required and maintained throughout the period of performance.
  • Public trust suitability; background investigation cleared prior to beginning performance.
  • Government-required training to be completed within 5 business days of start: NOAA IT Security, NOAA Safety, Sexual Assault/Sexual Harassment Prevention & Response (NAM 1330-52.222-70(b)(6)), and Records Management 101.

RESPONSIBILITIES:

Required (Deliverables):

  • All analyses conducted with accepted methods and QA/QC.
  • Assigned statistical and biological modeling components completed and integrated into COMPASS and life cycle models for the Columbia River basin, and others as needed.
  • Reproducible analytical workflows documented; modeling scripts, methods, and results shared via open-science platforms (e.g., GitHub).
  • Written status reports and other ad hoc communications; participation in field tasks as needed.

SKILLS:

Required:

  • Extensive experience in modeling and data analysis; extensive experience executing statistical analysis and modeling in R, with strong R coding skills.
  • Familiarity interpreting or interfacing with C or C++ code within a scientific modeling context.
  • Familiarity with common workplace software such as Google Suite and Microsoft Office.
  • Excellent communication skills; experience writing reports and contributing to peer-reviewed articles; able to work independently and on interdisciplinary teams.

  • Desired:

    • Experience with Bayesian statistical methods and mark-recapture analysis preferred.
    • Computational experience with command-line environments (e.g., Linux/shell scripting) preferred; experience with open-science concepts.
    • Experience with Bayesian modeling programs Stan and JAGS preferred.

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