Fraud Sr Data Scientist, Graph Analytics & Threat Intelligence

Our Mission

Our mission is to SAVE AND IMPROVE LIVES BY EMPOWERING HEALTHCARE CONSUMERS. Come be part of remarkable.

Overview

How you can make a difference  

 

You will be the architect of our next-generation threat-hunting and fraud-ring-detection capabilities—building graph-based analytics pipelines and Generative AI assistants that spot hidden networks of bad actors before losses occur. You will also help drive our Fraud & Security GenAI portfolio, deliver interactive chatbots, narrative generators, and automated playbooks that empower analysts to move at machine speed. This is a game-changing role: you’ll fuse transactional, identity, and threat-intel data into actionable network insights, partner on coordinated takedowns with Investigations and law enforcement, and set the vision for how HealthEquity outsmarts organized fraud.

 

What you’ll be doing

• Graph & Network Modeling: Design and productionize end-to-end pipelines that ingest transactions, identity records, and external intelligence into a graph store. Implement community detection, centrality scoring, and path-analysis algorithms to surface rings of colluding accounts or synthetic identities.
• GenAI Assistant Development: Lead Development of retrieval-augmented LLM tools to answer analyst queries (“Show me all accounts linked to this phone”), auto-summarize case dossiers, and recommend next investigative steps. Continuously refine prompts, vector stores, and retrieval strategies for high precision in a fraud context.
• Threat Hunting & Dashboards: Build interactive notebooks and visualizations for ad-hoc threat exploration—enabling analysts to pivot from summary graphs to transaction-level detail in seconds. Define and track KPIs: time-to-detect, ring-size reduction, and take-down success rates.
• Cross-Functional Collaboration & Takedowns: Partner with Internal Investigations, FBI, and Secret Service on evidence gathering and synchronized fraud-ring takedown operations. Ingest post-takedown intel to retrain models and evolve detection patterns.
• Innovation & Mentorship: Prototype advanced techniques (graph neural networks, anomaly detection) to predict emerging attack tactics. Mentor junior data scientists on graph theory, MLOps best practices, and GenAI usage.
• Sample Success Metrics Detection of top fraud rings pre-funding, reducing associated losses by target. Decrease in time investigators spend manually linking entities by target. Accuracy on synthetic-ID cluster classification by target.

What you will need to be successful

• Master’s or Ph.D. in Data Science, Computer Science, Applied Math, or related.
• Expertise in fraud or security analytics focused on graph or network methods.
• Expert in Python, SQL, and graph frameworks.
• Strong data engineering skills building ETL pipelines, managing large-scale datasets, and ensuring data quality
• Demonstrated ability to translate complex analytical results into clear, actionable insights
• Experience with MLOPs frameworks for model versioning, monitoring, and automated retraining
• Strong communicator with a track record of driving cross-team initiatives. 
• Experience with deepfake detection and adversarial-resilient modeling.
• Hands-on experience designing and deploying retrieval-augmented GenAI (LLM integration, vector search) solutions in an enterprise setting.
• Background and expertise in fintech, EFT, AML, payment-card fraud analytics.
• Proven collaboration in high-urgency environments, able to support live investigations and coordinate rapid takedowns.
• Prior work (open source, or academic publications) around analytics or security AI portfolio and usecases

#LI-Remote

This is a remote position.

Salary Range

$137,500.00 To $227,000.00 / year

Benefits & Perks

The actual compensation offer is determined based on job-related knowledge, education, skills, experience, and work location. This position will be eligible for performance-based incentives as part of the total compensation package, in addition to a full range of benefits including:  

• Medical, dental, and vision 

• HSA contribution and match 

• Dependent care FSA match 

• Uncapped paid time off 

• Paid parental leave 

• 401(k) match 

• Personal and healthcare financial literacy programs 

• Ongoing education & tuition assistance 

• Gym and fitness reimbursement 

• Wellness program incentives 
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