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Bayesian Modeling Jobs in Washington, DC (NOW HIRING)

Team Velocity

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

Develop predictive models including churn, propensity, lead scoring, customer lifetime value ... Regression, Bayesian methods, hypothesis testing, experimental design, time series, causal ...

Team Velocity

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

Develop predictive models including churn, propensity, lead scoring, customer lifetime value ... Regression, Bayesian methods, hypothesis testing, experimental design, time series, causal ...

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All JobsBayesian Modeling JobsBayesian Modeling Jobs in Washington, DC

Bayesian Modeling information

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How much do bayesian modeling jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for bayesian modeling in Washington, DC is $66.50, according to ZipRecruiter salary data. Most workers in this role earn between $59.62 and $77.31 per hour, depending on experience, location, and employer.

What is the difference between Bayesian Modeling vs Data Scientist?

AspectBayesian ModelingData Scientist
Required CredentialsStatistics, Mathematics, Data AnalysisStatistics, Computer Science, Data Analysis
Work EnvironmentResearch-focused, statistical modelingCross-functional, data analysis, visualization
Industry UsageResearch, academia, specialized analyticsBusiness, tech, finance, healthcare
Common Search/ComparisonYesYes

Bayesian Modeling and Data Scientists often overlap in skills like statistics and data analysis. Bayesian Modeling specializes in probabilistic models and statistical inference, while Data Scientists have broader roles including data cleaning, visualization, and machine learning. Both roles are essential in data-driven industries, but Bayesian Modeling is more focused on advanced statistical techniques.

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

To thrive as a Bayesian Modeler, you need a solid background in statistics, probability theory, and mathematical modeling, often supported by an advanced degree in statistics, mathematics, or a related field. Proficiency with programming languages such as R, Python, or Stan, and experience with statistical software and Bayesian inference tools are essential. Strong analytical thinking, attention to detail, and effective communication skills help in interpreting results and collaborating with multidisciplinary teams. These skills ensure accurate model development, reliable data-driven insights, and clear communication of complex findings to stakeholders.

How does a Bayesian modeling specialist typically collaborate with cross-functional teams in a workplace setting?

Bayesian Modeling specialists often work closely with data scientists, software engineers, and domain experts to integrate probabilistic models into larger analytical or production systems. They are involved in translating complex statistical concepts into actionable insights and recommendations tailored to business needs. Effective communication is key, as they must present findings to both technical and non-technical stakeholders, ensuring that model assumptions and results are clearly understood. Collaboration may also include contributing to code reviews, sharing best practices for model validation, and mentoring colleagues on Bayesian methodologies.

What is Bayesian modeling?

Bayesian modeling is a statistical approach that uses Bayes' Theorem to update the probability of a hypothesis as more data becomes available. It incorporates prior beliefs or knowledge, combines them with observed data, and produces a posterior probability distribution to guide inference and decision-making. This approach is widely used in various fields such as machine learning, data science, and scientific research for tasks like parameter estimation, prediction, and model selection.
What are popular job titles related to Bayesian Modeling jobs in Washington, DC? For Bayesian Modeling jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Bayesian Modeling jobs in Washington, DC look for? The top searched job categories for Bayesian Modeling jobs in Washington, DC are:
Bayesian Modeling jobs near you

Senior Data Scientist (Fraud Detection and Investigative Analytics)

Node.Digital

Washington, DC • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 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+ years Designing, implementing, and maintaining advanced AI systems and predictive models, including both supervised and unsupervised models.
  • 5+ years Developing analytic rules and models using leading edge analytic tools and best practices.
  • 5+ years Developing regression, classification, and other statistical models to identify anomalies, patterns, and predictive variables.
  • 3+ years Providing data support for criminal investigations into financial fraud or abuse of government funds.
  • 3+ years Manipulating data in Python. Pandas is required.
  • 3+ years Working in a modern cloud environment: Azure, AWS, or GCP. Certifications preferred.
  • 2+ years Conducting advanced data analysis in SQL, specifically SQL Server and PostgreSQL.
  • 2+ years Developing and scaling natural language processing solutions.
  • 2+ years Presenting 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

Apply