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

Data Scientist - Fraud Analytics - Austin TX (100% Onsite)

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