Data Scientist – Fraud Detection & Analytics

TISTA Science and Technology Corporation

13d • Remote

About The Position

TISTA is seeking a Data Scientist to design and implement advanced analytics and machine learning solutions that strengthen fraud detection and improper payment risk management for the Veterans Benefits Administration (VBA). Future Opportunity: This posting is for future consideration and is not an active hiring effort. By joining our talent pool, you’ll receive updates and early notification when openings become available.

Requirements

• Minimum: 3–5 years of experience in data science or machine learning, with a focus on fraud detection or risk analytics.
• Strong proficiency in Python and libraries such as scikit-learn, TensorFlow, or PyTorch.
• Hands-on experience with feature engineering, model tuning, and statistical analysis.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and CI/CD practices for ML deployment.
• Expertise in machine learning algorithms and statistical modeling.
• Ability to translate complex data insights into actionable recommendations.
• Strong collaboration skills across technical and operational teams.
• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• The ability to pass a Tier 2/Modest Background Investigation.

Nice To Haves

• Master’s degree in Data Science, Machine Learning, or Artificial Intelligence.
• Certifications such as AWS Machine Learning Specialty or Certified Fraud Examiner (CFE) are a plus.

Responsibilities

• Build, train, evaluate, and tune machine learning models for fraud detection and payment integrity risk scoring.
• Conduct feature engineering, statistical modeling, and pattern analysis to identify anomalies and fraud typologies.
• Support research and development activities, including prototype development and model enhancement.
• Collaborate with engineers and analysts to integrate models into production workflows and ensure scalability.

What This Job Offers

• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees