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Data Scientist Fraud Analytics & Investigative Support - Praescient Analytics
Data Scientist
Data Scientists will design, test, and deploy advanced fraud‑analytics solutions for federal benefit programs, using statistical modeling, machine learning, and data visualization to detect waste, abuse, and mismanagement.
About the role
Key Responsibilities
- Develop and validate predictive models and statistical algorithms to identify fraudulent activity across large‑scale government programs.
- Perform data extraction, cleaning, and transformation using SQL and programming languages such as Python or R.
- Create interactive visualizations and dashboards to communicate findings to investigators and senior stakeholders.
- Implement entity‑resolution techniques to link disparate data sources and uncover hidden relationships.
- Collaborate with multidisciplinary teams to integrate analytical solutions into operational workflows and support investigative case work.
- Document methodology, maintain reproducible code, and ensure models meet compliance and security standards.
Requirements
- Advanced degree (M.S. or Ph.D.) in Data Science, Statistics, Computer Science, or a related quantitative field.
- Proficiency in Python or R for statistical analysis and machine‑learning model development.
- Strong SQL skills for querying large relational databases.
- Experience with machine‑learning frameworks, statistical modeling, and data‑visualization tools (e.g., Tableau, Power BI, matplotlib, ggplot2).
- Demonstrated ability to apply entity‑resolution or network‑analysis techniques to complex, multi‑source datasets.
Skills
pythonsqlmachine learning