Data Scientist - Fraud Analytics

Role: Data Scientist - Fraud Analytics

Location: Austin, TX (100% Onsite)

Experience: 8-12 Years

Job Summary: We are looking for a Lead Data Scientist with strong expertise in Fraud Analytics, Machine Learning, and AI-driven fraud detection solutions.

The ideal candidate will lead end-to-end fraud use case discovery, model development, feature engineering, and deployment of advanced fraud detection systems leveraging ML, Graph Analytics, and AI techniques.

Required Skills

Primary Skills

• Fraud Analytics
• Machine Learning
• Graph Analytics
• Feature Engineering
• Dataiku
• Agentic AI Architecture

Secondary Skills

• Neo4j
• Python
• Model Explainability
• Statistics
• Experimentation Frameworks

Key Responsibilities

• Lead fraud use case discovery and scenario design.
• Define fraud detection strategies using business rules, Machine Learning, and graph techniques.
• Identify predictive variables and build fraud feature catalogues.
• Build and validate pilot fraud detection models.
• Optimize precision, recall, and fraud catch rates.
• Collaborate with engineering teams on low-latency scoring architectures.
• Drive model explainability, governance, and compliance initiatives.
• Support shadow runs and challenger model validation against existing systems.

Responsibilities Area

• Data Science & AI Strategy
• Solution Design & Model Development
• Fraud Analytics & Investigation Insights
• Technical Leadership
• Team Mentoring & Stakeholder Management

Regards,

Gaurav Tripathi

Sr Associate Talent Acquisition

KAnand Corporation

Email: