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Postdoctoral In Bayesian Statistics Jobs in Seattle, WA

Exponent Inc.

Statistical Scientist (Ph.D.)

Bellevue, WA · On-site

$133K - $150K/yr

Thanks for your interest in joining our team! Key statistics: * 950+ Consultants * 640+ Ph.D.s * 90 ... Bayesian statistics, machine learning, or quality control/improvement * Minimum of 2 years ...

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Competitive Intelligence Research

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 ...

Meta

Competitive Intelligence Research

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 ...

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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 Jun 26, 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 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 the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Bayesian Statistics, and why are they important?

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.
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Postdoctoral In Bayesian Statistics jobs near you
Sr. Developer

Sr. Developer

Avani Technology Solutions, Inc.

Bellevue, WA • On-site

Contractor

This job post has expired today. Applications are no longer accepted.

Job description

Advanced knowledge in machine learning, computer science, math, statistics or a related discipline Extensive data modeling and machine learning architecture skills Programming experience in Python, R or Java Background in machine learning Frameworks such as: TensorFlow or Keras Knowledge of Hadoop or another distributed computing systems Experience working in an Agile environment Advanced math skills linear algebra, Bayesian statistics group theory Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability Exploring and visualizing data to gain an understanding of it then identifying differences in data distribution that could affect performance when deploying the model in the real world Verifying data quality and/or ensuring it via data cleaning, Supervising the data acquisition process if more data is needed, Finding available datasets online that could be used for training Defining validation strategies, Defining the preprocessing or feature engineering to be done on a given dataset Defining data augmentation pipelines, Training models and tuning their hyperparameters Analyzing the errors of the model and designing strategies to overcome them Deploying models to production Strong written and verbal communications
Hours : 8:00am to 5:00pm
Education :
Additional Job Details : Primary skil: Azure Machine Learning/Python/R

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