Senior Member Risk & Experience Analyst

SoFi•Jacksonville, FL

About The Position

SoFi’s Fraud Management team is looking for a data-driven analyst to bridge the gap between risk mitigation and member advocacy. This role is dedicated to identifying and offboarding "bad actors" already on the books before they can inflict further financial or reputational damage, and how the subsequent fraud and dispute process impacts our members. While we remain member-centric, this role acknowledges that the best way to serve our legitimate members is to remove the bad ones. Your mission is twofold: Protect the House by identifying and offboarding high-risk actors, and Empower the Member by driving NPS and First Call Resolution (FCR) through rigorous root-cause analysis.

Requirements

Bachelor or advanced degree in Statistics, Business Analytics, Math or Economics.
Strong data technical skills on databases, Excel/SQL/Python and data dashboard tools.
Able to use different types of data to define business needs
Highly motivated to drive change, eager to learn and create new things from scratch and able to work collaboratively in a complex and fluid environment.
Experience of developing analysis structure using different data sources and analytical methods to meet business needs.
Capability of defining and building business metrics and dashboard infrastructures and know how to automate the manual process to improve efficiency.
Able to connect the dots between data and businesses to provide meaningful insights and actionable enhancements.
Knows how to troubleshoot data and metrics gaps and be innovative to solve both technical and business problems
Very strong communication skills by connecting the dots with the big picture with data and facts to support the story.

Responsibilities

Analyze member feedback and Net Promoter Scores (NPS) specifically related to fraud and dispute touchpoints. Identify "friction points" where our security protocols may be alienating legitimate members and recommend data-driven adjustments.
Conduct comprehensive forensic analysis of existing fraud and dispute workflows. Use SQL and behavioral data to identify "sleeper" accounts and high risk members, while simultaneously pinpointing bottlenecks that negatively impact NPS and FCR.
Apply data-driven criteria to identify high-risk members for offboarding. Prepare the data sets for adverse action, ensuring we exit "bad members" based on clear evidence of behavioral or dispute-related risk. Reporting on impacts to the business.
Prepare cost-benefit analyses that justify the prioritization of fraud prevention and member experience. Quantify the ROI of a "Member-First" friction reduction strategy, showing how improved FCR and NPS lead to higher member retention, reduce complaints, and lower operational costs.
Continuously monitor the "health" of the fraud and dispute ecosystem. Identify and document a backlog of new opportunities for risk reduction and experience improvement, ensuring stakeholders are aware of emerging trends that require future attention.