Data Scientist at Elder Research in Arlington, VA

Job description

• Elder Research Inc., a wholly owned subsidiary of MANTECH international Corporation seeks a motivated, career and customer-oriented Data Scientist to join our team in Arlington, VA. This role is a remote role preferably in the Washington DC area.
• As a Data Scientist, you will support the Internal Revenue Service’s mission to improve tax compliance, fraud detection, and risk identification across large, complex tax and financial data environments. You will work directly with government clients, program managers, and technical teams to understand business and compliance challenges, design analytical approaches, and deliver data-driven solutions that inform enforcement, audit prioritization, and fraud prevention efforts.
• In this role, you will develop, test, and deploy predictive and statistical models using structured and unstructured data to identify anomalies, non-compliance risk, and potential fraud within tax records and related datasets. You will contribute across the full data science lifecycle, from problem formulation and data exploration through model validation, deployment, and stakeholder communication.

Responsibilities

• Prior programming experience, preferably in Python or R, including data exploration, feature engineering, model development, and writing modular, reusable, well-documented code within an iterative development process that includes peer review and collaboration
• Demonstrated experience using Python, SQL, and Databricks for data analysis, modeling, statistical evaluation, and working with Markdown for technical documentation
• Explore, clean, and wrangle large, complex datasets to uncover insights and identify opportunities for data science–driven solutions in support of assessments, gap analyses, and actionable recommendations for IRS stakeholders
• Design, develop, test, validate, and implement quantitative and qualitative data science solutions and predictive risk models (including audit selection, refund review, and fraud prevention initiatives) that are modular, maintainable, adaptable to evolving government and regulatory requirements, and supported by robustness, sensitivity, and significance testing to ensure defensible and explainable results
• Apply statistical and machine learning techniques (supervised and unsupervised) to anomaly detection, fraud identification, and non-compliance risk scoring to help prioritize cases based on compliance risk, fraud indicators, and business impact
• Collaborate with clients, subject matter experts, and cross-functional teams to refine problem statements, requirements, and analytical approaches, while demonstrating the ability to work independently in a collaborative, fast-paced environment
• Prepare and deliver technical and non-technical briefings, reports, and presentations to audiences with varying levels of analytical sophistication, translating business and compliance needs into technical solutions with strong interpersonal, written, and verbal communication skills

Requirements

• Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences
• 2-10+ years of experience in data science, analytics, or a related technical field
• Experience using version control systems (e.g., Git) and collaborative development practices
• Strong understanding of relational databases and SQL
• Comfortable learning new tools, methodologies, and domains, including working outside your comfort zone
• Strong analytical mindset with a willingness to tackle complex mathematical and statistical challenges
• Willingness to travel and work on-site at client locations as required by project needs
• Must currently possess an IRS Public Trust clearance with Full Background Investigation
• Advanced degree (MS or PhD) in statistics, computer science, data science, mathematics, analytics, engineering, or related fields; experience applying advanced statistical concepts including sampling considerations, bias detection, weighting techniques, handling missing or outlier data, exploratory analysis, and longitudinal forecasting; and understanding of the data analytics lifecycle (e.g., CRISP-DM)
• Experience with PySpark, Unity Catalog, and Jobs in Databricks, with familiarity using platforms and tools such as Databricks and AWS
• Experience with Natural Language Processing (NLP) and text analytics applied to unstructured documents or case notes, as well as graph analytics and network analysis to identify relationships, fraud rings, or interconnected entities
• Experience with containerization and environment management (e.g., venv, conda)
• Experience operating in secure or remote government environments, including use of bash and command-line tools

Skills

Required

• Python or R
• SQL
• Databricks
• Version control systems (e.g., Git)
• Analytical mindset
• Willingness to travel and work on-site

Preferred

• PySpark
• Unity Catalog
• Databricks Jobs
• AWS
• Natural Language Processing (NLP)
• Text analytics
• Graph analytics and network analysis
• Bash and command-line tools