Data Scientist (Fraud Analytics & Investigative Support)

Summary

Praescient Analytics is seeking multiple Data Scientists to support advanced fraud analytics and investigative initiatives for a federal oversight organization. The role involves developing and deploying analytical solutions to identify fraud and support decision-making across government-funded initiatives.

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

Skills

• 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
• Fraud detection, fraud prevention, financial crime analytics, or program integrity
• Federal benefit programs, grants, loans, healthcare, unemployment insurance, emergency assistance, disaster relief, or other public-sector programs
• Risk modeling, anomaly detection, entity resolution, predictive analytics, and statistical modeling
• Cloud analytics environments such as Azure Databricks, Microsoft SQL Server, Microsoft Fabric, Azure Data Lake Storage (ADLS), Power BI, Git repositories, or Lakehouse architectures
• Working with public, non-public, commercial, financial, or cross-agency datasets
• Data visualization and dashboard development
• Agile software development and analytics teams
• Enterprise data governance, metadata management, and data quality best practices

Qualifications

Must Haves

• 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

Nice to Haves

• Fraud detection, fraud prevention, financial crime analytics, or program integrity
• Federal benefit programs, grants, loans, healthcare, unemployment insurance, emergency assistance, disaster relief, or other public-sector programs
• Risk modeling, anomaly detection, entity resolution, predictive analytics, and statistical modeling
• Cloud analytics environments such as Azure Databricks, Microsoft SQL Server, Microsoft Fabric, Azure Data Lake Storage (ADLS), Power BI, Git repositories, or Lakehouse architectures
• Working with public, non-public, commercial, financial, or cross-agency datasets
• Data visualization and dashboard development
• Agile software development and analytics teams
• Enterprise data governance, metadata management, and data quality best practices

Benefits

• 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