1

Bayesian Jobs in Washington (NOW HIRING)

Deep knowledge of mathematical statistics, maximum likelihood estimation, sufficient statistics, hypothesis testing theory, Bayesian inference, regression analysis, multivariate methods, experimental ...

Deep knowledge of mathematical statistics, maximum likelihood estimation, sufficient statistics, hypothesis testing theory, Bayesian inference, regression analysis, multivariate methods, experimental ...

Showing results 41-60

Bayesian information

See Washington salary details

$160.5K

$171.8K

$184.1K

How much do bayesian jobs pay per year?

As of Sep 4, 2026, the average yearly pay for bayesian in Washington is $171,786.00, according to ZipRecruiter salary data. Most workers in this role earn between $166,418.00 and $177,154.00 per year, depending on experience, location, and employer.

What is a Bayesian?

A Bayesian job typically involves applying Bayesian statistics, probabilistic modeling, and inference techniques to analyze data and make decisions under uncertainty. Professionals in this field use Bayes' theorem to update beliefs based on new evidence, often working in areas like machine learning, finance, healthcare, and research. Common roles include Bayesian statisticians, data scientists, and researchers who build probabilistic models to improve predictions and decision-making.

What are the typical projects or challenges faced in a Bayesian role?

In a Bayesian role, you’ll often work on projects involving probabilistic modeling, uncertainty quantification, and predictive analytics for real-world decision-making. Common challenges include structuring prior distributions, ensuring computational efficiency for complex models, and clearly explaining Bayesian results to non-technical stakeholders. You might collaborate closely with data engineers, domain experts, and business analysts to refine models and translate findings into actionable recommendations. This role offers the opportunity to tackle diverse analytical problems across industries like healthcare, finance, or tech, supporting ongoing professional growth and learning.

What are the key skills and qualifications needed to thrive in a Bayesian role, and why are they important?

To thrive as a Bayesian (typically a Bayesian Data Scientist or Statistician), you need a strong background in probability theory, statistical modeling, and mathematics, often with an advanced degree in statistics, data science, or a related quantitative field. Experience with programming languages such as Python or R, Bayesian analysis libraries (e.g., Stan, PyMC), and familiarity with statistical software are commonly required. Analytical thinking, collaborative teamwork, and the ability to communicate complex results clearly are valuable soft skills in this role. These abilities are essential for designing robust models, interpreting data accurately, and delivering actionable insights to interdisciplinary teams.

What are the most commonly searched types of Bayesian jobs in Washington?

The most popular types of Bayesian jobs in Washington are:

Infographic showing various Bayesian job openings in Washington as of August 2026, with employment types broken down into 75% Full Time, 17% Part Time, 2% Temporary, and 6% Contract. Highlights an 54% Physical, 4% Hybrid, and 42% Remote job distribution, with an average salary of $171,786 per year, or $82.6 per hour.

Senior Data Scientist (Fraud Detection and Investigative Analytics)

Node.Digital

Washington, DC • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 5 days ago


Job description

Senior Data Scientist (Fraud Detection and Investigative Analytics)

Location: Herndon, VA (Remote Work)

Must have an Public Trust Clearance

KEY RESPONSIBILITIES

  • Review, maintain, and extend all existing loan fraud indicators developed by TSD, and provide authoritative expertise on analytic method selection.
  • Design, develop, test, calibrate, and implement advanced statistical and machine learning models targeting financial fraud, improper payments, and non compliance within SBA programs.
  • Build and refine both supervised and unsupervised models, including regression, Bayesian, clustering, and ensemble approaches, and tune candidate models to determine best fit.
  • Perform data quality analysis on source tables to identify abnormalities and inconsistencies, and develop repeatable processes for combining and analyzing large relational, structured, and unstructured sources.
  • Collaborate directly with criminal investigators to determine and execute analytic strategies supporting loan fraud cases, adapting analysis as case needs shift and proactively surfacing data quality issues.
  • Adhere closely to the federal rules of criminal procedure governing protected information, including Rule 6(e).
  • Develop case leads for SBA OIG investigations from model outcomes.
  • Document all methodology, test models, and production models in a form that satisfies criminal evidentiary requirements.
  • Build visualizations and dashboards that convey methodological choices, outcomes, and predictive capability, and iterate them on end user feedback.
  • Deliver findings in multiple registers: data summaries and visualizations for investigative staff, executive summaries for OIG leadership.
  • Coordinate with the data engineering seat so the architecture supports machine learning efficiently.
  • Create programming and automation techniques that improve task efficiency using SharePoint, Python, Excel, Power BI, Power Apps, and similar tools.
  • Identify new business questions that expand the scope of analysis and reporting.

Requirements

Required:

Education

Master's, Ph.D., or doctorate level equivalent degree in data science, machine learning, computer science, mathematics, or a related field. Alternatively, ten years of applied work experience in any of the same fields.

  • 5+ yearsDesigning, implementing, and maintaining advanced AI systems and predictive models, including both supervised and unsupervised models.
  • 5+ yearsDeveloping analytic rules and models using leading edge analytic tools and best practices.
  • 5+ yearsDeveloping regression, classification, and other statistical models to identify anomalies, patterns, and predictive variables.
  • 3+ yearsProviding data support for criminal investigations into financial fraud or abuse of government funds.
  • 3+ yearsManipulating data in Python. Pandas is required.
  • 3+ yearsWorking in a modern cloud environment: Azure, AWS, or GCP. Certifications preferred.
  • 2+ yearsConducting advanced data analysis in SQL, specifically SQL Server and PostgreSQL.
  • 2+ yearsDeveloping and scaling natural language processing solutions.
  • 2+ yearsPresenting methods and findings to technical and non technical stakeholders, both orally and in written products and visualizations.

PREFERRED QUALIFICATIONS

  • Cloud certification in Azure, AWS, or GCP.
  • Direct experience with SBA loan programs, including 7(a), 504, EIDL, or PPP, or with comparable federal lending or grant fraud.
  • Entity resolution, record linkage, or graph and network analysis applied to fraud.
  • Experience producing analytic products that were used in a criminal referral or prosecution.
  • Model explainability practice such as SHAP or comparable feature attribution methods.

Benefits

We are proud to offer competitive compensation and benefits packages to include

  • Medical 
  • Dental
  • Vision
  • Basic Life 
  • Health Saving Account
  • 401K matching
  • Three weeks of PTO/Sick
  • 11 Paid Holidays
  • Pre-Approved Online Training