Fraud Model Developer
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Job Location:
Jacksonville, FL - USA
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
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Who we are:
Shape a brighter financial future with us.
Together with our members were changing the way people think about and interact with personal finance.
Were a next-generation financial services company and national bank using innovative mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation and were at the forefront. Were proud to come to work every day knowing that what we do has a direct impact on peoples lives with our core values guiding us every step of the way. Join us to invest in yourself your career and the financial world.
The role:
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
What youll do:
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
What youll need:
- 7 years of advanced quantitative modeling experience or
- Masters 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
Nice to have:
- Direct experience in fintech banking payments or digital fraud risk
- Familiarity with graph databases and network-based fraud detection
- Experience developing and deploying models in AWS environments
- Experience influencing fraud policy or risk tolerance decisions
Required Experience:
IC
Key Skills
About Company
Why do 10M+ members trust SoFi? Financial solutions for school, marriage, starting a family, home buying, retirement, or whatever’s next. Member FDIC.
