Data Scientist

Role Overview

Elder Research is seeking a Data Scientist to support the Internal Revenue Service (IRS) mission to improve tax compliance, fraud detection, and risk identification using large, complex tax and financial datasets. This is a hybrid/remote role preferably in the Washington DC area (Arlington, VA), with potential travel and on-site work as required.

Responsibilities

• Develop, test, and deploy predictive and statistical models using structured and unstructured data to identify anomalies and potential fraud.
• Support the full data science lifecycle: problem formulation → data exploration → validation → deployment → stakeholder communication.
• Perform data exploration, cleaning, and wrangling on large datasets to uncover insights and identify data science opportunities.
• Build quantitative and qualitative solutions and predictive risk models (e.g., audit selection, refund review, fraud prevention).
• Apply statistical and machine learning methods (both supervised and unsupervised) for:
  • anomaly detection
  • fraud identification
  • non-compliance risk scoring and prioritization
• Ensure models are robust, sensitive, and statistically significant, producing defensible and explainable results.
• Collaborate with government clients, program managers, and technical teams to refine requirements and analytical approaches.
• Prepare technical and non-technical briefings, reports, and presentations for varied audiences.
• Write modular, reusable, well-documented code and participate in peer review and iterative collaboration.

Requirements (Minimum)

• 2–10+ years of experience in data science/analytics (or related technical field).
• Prior programming experience, preferably in Python or R, including:
  • data exploration
  • feature engineering
  • model development
  • modular, reusable code in an iterative, peer-reviewed process
• Demonstrated experience with Python, SQL, and Databricks for analysis and modeling.
• Strong working knowledge of relational databases and SQL.
• Experience with version control (e.g., Git) and collaborative development practices.
• Ability to learn new tools/methods/domains and work independently in a fast-paced environment.
• Strong analytical mindset for complex mathematical and statistical problems.
• Travel and on-site work as needed by project requirements.
• Security clearance required: IRS MBI.

Preferred Qualifications

• MS or PhD in statistics, computer science, or a related field.

Key Tools/Methods

• Predictive modeling, statistical evaluation, anomaly detection, supervised/unsupervised ML
• Robustness/sensitivity/significance testing and explainability
• Technical documentation (Markdown)