Data Scientist (Fraud Analytics & Investigative Support)

Role Description

Praescient Analytics is seeking multiple Data Scientists to support advanced fraud analytics and investigative initiatives for a federal oversight organization. These positions will develop, test, validate, and deploy innovative analytical solutions that help identify fraud, waste, abuse, and mismanagement across large-scale federal benefit programs and other government-funded initiatives.

Working as part of a multidisciplinary analytics team, Data Scientists will leverage statistical analysis, machine learning, data visualization, entity resolution, and risk modeling techniques to transform large, diverse datasets into actionable intelligence supporting investigators, auditors, and government decision-makers.

The ideal candidate is a technically strong, mission-focused data scientist who enjoys solving complex analytical problems while collaborating with investigators, business analysts, data engineers, forensic accountants, and government stakeholders.

Key Responsibilities

• Develop, test, validate, and maintain fraud detection and program integrity analytics.
• Design analytical rules and methodologies to identify fraud indicators, anomalies, suspicious activity, and emerging risks.
• Perform exploratory data analysis, feature engineering, model development, validation, and performance evaluation.
• Analyze structured and unstructured data from multiple public, non-public, commercial, financial, and government data sources.
• Collaborate with Data Engineers to prepare and optimize data for analytics.
• Support entity resolution, anomaly detection, predictive analytics, and risk scoring initiatives.
• Produce dashboards, reports, visualizations, and analytical products that support investigative decision-making.
• Document analytical methodologies, assumptions, validation results, and technical findings.
• Participate in Agile delivery activities including sprint planning, demonstrations, peer reviews, and iterative model development.

Qualifications

• Must have experience with Fraud Analysis.
• Three (3) or more years of professional experience in data science, applied analytics, machine learning, statistics, fraud analytics, or a related quantitative field.
• Strong programming experience using Python and SQL.
• Experience developing and validating analytical models.
• Experience analyzing structured and unstructured datasets.
• Experience documenting analytical methodologies and technical findings.
• Strong analytical reasoning and problem-solving skills.
• Excellent written and verbal communication skills.

Preferred Qualifications

• Experience in fraud detection, fraud prevention, financial crime analytics, or program integrity.
• Familiarity with federal benefit programs, grants, loans, healthcare, unemployment insurance, emergency assistance, disaster relief, or other public-sector programs.
• Knowledge of risk modeling, anomaly detection, entity resolution, predictive analytics, and statistical modeling.
• Experience with cloud analytics environments such as Azure Databricks, Microsoft SQL Server, Microsoft Fabric, Azure Data Lake Storage (ADLS), Power BI, Git repositories, or Lakehouse architectures.
• Experience working with public, non-public, commercial, financial, or cross-agency datasets.
• Skills in data visualization and dashboard development.
• Experience in Agile software development and analytics teams.
• Understanding of enterprise data governance, metadata management, and data quality best practices.

Benefits

• Competitive salary based on qualifications and experience.
• Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles).
• 401(k) with company match.
• Travel & performance incentives.
• 3 weeks paid time off (plus Federal Holidays).
• $5K annual training allowance.
• $500 book allowance.
• Tuition reimbursement program.