Fraud Model Developer

Jacksonville, FL; Cottonwood Heights, UTFull-TimeMid-levelOther

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Shape a brighter financial future with us.
Together with our members, we’re changing the way people think about and interact with personal finance.

We are looking for a Senior Data Scientist and/or Machine Learning Model Developer to join our Fraud Model Development Team. This role owns end-to-end design, development, validation, deployment partnership, and performance management of high-impact fraud models across SoFi products including Personal Loans, Student Loans, Credit Cards, and Crypto.
The Senior Fraud Model Developer is accountable for measurable fraud loss reduction and false positive improvements within assigned domains. This individual partners closely with Fraud Prevention, Risk, Operations, Finance, Compliance, and ML Platform teams to influence fraud strategy, inform risk tolerance decisions, and ensure models deliver sustained business impact.
This position requires deep expertise in data analytics, statistical modeling, and machine learning, along with the ability to translate complex model performance into clear business outcomes. The ideal candidate brings strong fraud domain knowledge, production ML experience, and a demonstrated ability to manage model risk and complexity at scale

The Senior Fraud Model Developer will help SoFi build and scale high-performing fraud modeling solutions by:
Owning end-to-end development of fraud models within assigned product or risk domains, from problem framing through production deployment and ongoing monitoring
Driving measurable reductions in fraud loss, false positives, and operational expenses
Translating model outputs into business impact metrics and influencing fraud strategy decisions
Aggregating and synthesizing datasets from multiple data environments to design scalable and reusable modeling frameworks
Analyzing complex datasets to identify drivers of fraud loss and member friction across products
Conducting trade-off analysis between fraud loss mitigation, customer experience, and regulatory guardrails
Establishing and maintaining model monitoring standards (e.g., performance metrics, drift detection, recalibration cadence) to proactively manage model risk
Investigating external risk data and emerging fraud patterns to inform roadmap prioritization
Partnering with ML Platform teams to productionize models in AWS and improve lifecycle governance
Reducing model development cycle time by simplifying processes, improving documentation rigor, and creating reusable components
Handling escalations related to model performance, risk exposure, or business impact within assigned scope
Influencing roadmap sequencing and contributing to prioritization discussions based on ROI, regulatory considerations, and level of effort

7+ years of advanced quantitative modeling experience, or
Master’s degree and 5+ years of related experience, or
PhD and 3+ years of related experience, or
Equivalent practical experience
Demonstrated ownership of production machine learning models with measurable impact on fraud loss or false positive reduction
Deep expertise in Python, SQL, and data visualization tools (e.g., Tableau)
Strong knowledge of statistical methodologies and machine learning techniques (e.g., regression, decision trees, gradient boosting, random forests, neural networks, clustering analysis)
Experience designing, validating, and monitoring models using metrics such as AUC, KS, precision/recall, and drift detection
Ability to independently determine modeling approaches, manage trade-offs, and execute solutions with minimal guidance
Experience partnering cross-functionally with Risk, Fraud Ops, Engineering, Finance, and Compliance stakeholders
Strong communication skills with the ability to distill complex technical concepts into clear business recommendations
Demonstrated ability to manage risk exposure within projects and proactively escalate with proposed solutions
Master’s degree and 5+ years of related experience, or
PhD and 3+ years of related experience, or
Equivalent practical experience