Data Scientist

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.
• 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.

Qualifications

• Must currently possess an IRS Public Trust clearance with Full Background Investigation.

Physical Requirements

• Must be able to remain in a stationary position 50%.
• Frequent communication with co-workers, management, and customers, which may involve delivering presentations.
• Must be able to exchange accurate information in these situations.

About Elder Research, Inc

Elder Research considers all qualified applicants for employment without regard to disability or veteran status or any other status protected under any federal, state, or local law or regulation. If you need a reasonable accommodation to apply for a position with Elder Research, please email us at careers@elderresearch.com and provide your name and contact information.