Fraud Data Scientist, AIML Modeling & GenAI

HealthEquity; Draper (UT); Remote; USD 115,000 - 180,000; Full time

Job summary

Join a forward-thinking company dedicated to empowering healthcare consumers through innovative technology. As a Fraud Data Scientist, you will drive predictive modeling for fraud detection and enhance security measures. Your expertise in AI and machine learning will be pivotal in developing GenAI solutions and integrating MLOps pipelines. With a commitment to continuous improvement and collaboration, this role offers a unique opportunity to make a significant impact in the fintech space. If you're passionate about leveraging technology to combat fraud and improve lives, this is the perfect role for you.

Benefits

Medical, dental, vision

HSA contribution and match

Dependent Care FSA match

Uncapped paid time off

Adventure accounts

Paid parental leave

401(k) match

Financial literacy programs

Ongoing education and tuition assistance

Gym and fitness reimbursements

Qualifications

• 3+ years of experience in AI/ML for fraud prevention.
• Experience with production MLOps pipelines for real-time inference.

Responsibilities

• Build models for fraud detection using supervised and unsupervised techniques.
• Design GenAI solutions for alert summarization and rule suggestions.

Skills

Python

SQL

Machine Learning

Predictive Modeling

Feature Engineering

Communication Skills

Fraud Prevention

Real-time Inference

Education

Master's or Ph.D. in Data Science

Tools

XGBoost

TensorFlow

PyTorch

Kafka

Spark

Job description

Fraud Data Scientist, AIML Modeling & GenAI

Job Locations

US-Remote

Our Mission

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

Overview

How you can make a difference

You will drive HealthEquity's predictive modeling for card fraud, money-movement scams, AML alerts, and account-takeover attacks. You will also help develop our GenAI portfolio for fraud and security, building models that predict fraud in real time, creating AI assistants that automate alert triage and policy drafting, and providing explainable insights for immediate containment and strategic controls. Your innovations will be crucial in reducing losses and enhancing our security posture.

What you'll be doing

1. Predictive Modeling & Feature Engineering: Build supervised (XGBoost, neural nets) and unsupervised (autoencoders, isolation forests) models for CNP, AML, and Account Takeover/identity fraud. Engineer features like device fingerprints, transaction sequences, behavior embeddings, geospatial velocity for real-time scoring.
2. GenAI Solutions: Design and fine-tune LLM-based assistants for alert summarization, rule suggestions, and MFA policy drafting. Manage vector stores and retrieval pipelines for rapid, accurate responses under load.
3. MLOps & Production Integration: Define the model lifecycle from data ingestion to deployment, monitoring, and retraining. Collaborate with teams to integrate inference endpoints into transaction gateways and streaming platforms.
4. Explainability & Compliance: Implement explainable AI frameworks for auditability. Partner with Compliance to document model risks and meet regulations.
5. Performance Metrics & Continuous Improvement: Establish dashboards for key metrics, iterate on models and prompts based on feedback from fraud investigations.

What you will need to be successful

• Master's or Ph.D. in Data Science, Machine Learning, Statistics, or related field.
• 3+ years applying AI/ML in fraud prevention, AML, or risk analytics.
• Proficiency in Python, SQL, ML frameworks (scikit-learn, XGBoost, TensorFlow/PyTorch), and LLM fine-tuning.
• Experience building production MLOps pipelines for real-time inference.
• Strong communication skills to articulate model logic and impact to diverse stakeholders.
• Deep knowledge of payment card networks, EFT systems, and money movement.
• Experience with streaming architectures (Kafka, Spark) and real-time feature stores.
• Prior experience with GenAI assistants in workflows or customer apps.
• Knowledge of software engineering best practices: code reviews, testing, CI/CD.
• Open-source contributions or publications in relevant fields.
• Experience in fintech or payments environments and a passion for staying ahead of adversaries.

#LI-Remote

This is a remote position.

Salary Range

$115,000 to $180,000 per year

Benefits & Perks

The actual compensation depends on experience and skills. Benefits include:

• Medical, dental, vision
• HSA contribution and match
• Dependent Care FSA match
• Uncapped paid time off
• Adventure accounts
• Paid parental leave
• 401(k) match
• Financial literacy programs
• Ongoing education and tuition assistance
• Gym and fitness reimbursements
• Wellness incentives

Why work with HealthEquity

Our vision is to make HSAs as popular as retirement accounts by 2030. We are committed to diversity and inclusion. We ensure equal opportunity employment and a drug-free workplace. For more info, visit our Careers page.

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