Senior Product Manager, Transactional Risk

The Role

At SoFi, we’re on a mission to help our members get their money right. We are seeking a high-agency Senior Product Manager to own the fraud product strategy for all money movement rails at SoFi.

You will be the core of the fraud organization, directly owning the real-time systems and detection logic that monitor and authorize all money movement at SoFi. Your mission is to stop bad actors from moving a single dollar out of the ecosystem while ensuring our good members can pay their bills and send money to friends without a hitch. Sitting at the intersection of Data Science, Engineering, and Payments, you will build high-precision detection logic that scales. You will own the risk profile for every inflow and outflow, building out defenses against the unique challenges of physical check fraud, ACH, Wires, Card, and irreversible real-time payments.

What You’ll Do

• Own the Transactional Roadmap: Define and execute the product strategy for transaction authorization and monitoring, both in-app and out-of-app.
• Harden the "Hot Path": Enable the rules and ML models that decide in milliseconds whether a transaction is safe, suspicious, or fraudulent.
• Drive Smarter Limits: Move beyond blunt "one-size-fits-all" limits. You will build and iterate on designing a secure solution in a limitless world, velocity policies, and transaction-time policy checks that adapt based on member risk and behavior.
• Design Pre-Authorization Gates: Own the logic for assessing member eligibility to attempt a transaction and strategically issuing step-up challenges before the transaction leaves our systems.
• Optimize Efficacy: You’ll tune our detection systems to maximize loss prevention while minimizing False Positives.
• Full-Rail Coverage: Own the fraud product strategy to secure all transactional money movement rails including ACH, Wires, Debit Card, Credit Card, Checks, P2P, International Remittances and Crypto.
• Cross-Functional Collaboration: Partner closely with the Fraud Products Lead to ensure your transactional logic fits into the holistic member risk profile, with the Account Security team who hands you a "Secured Session", and with the Fraud Data team for the features your rules rely on.
• Metrics & Impact: Manage and optimize key success metrics, including keeping Gross/Net Fraud Loss (BPS) below target, maintaining sub-second detection latency for real-time rails, and ensuring a low False Positive Rate (FPR) so we aren't blocking good members unnecessarily.

What You’ll Need

• 4+ years of Product Management experience: With a focus on fraud, risk, payments, or FinTech.
• Deep Domain Expertise in Fraud: You possess a strong understanding of common fraud attack vectors and the strategic product solutions required to mitigate them.
• Payments Expertise: You understand the nuances of different payment rails (ACH, Wires, Card) and how fraudsters exploit the "settlement gap" in each.
• A Data-First Decision Maker: You are comfortable diving into SQL or data visualization tools to understand why a specific rule fired and how to tighten the net without catching good users. You can synthesize inputs and data from multiple sources to build a strategic rationale that advocates for long-term customer value.
• Systems Thinker: You don't just want to write a rule; you want to build a repeatable framework for how we authorize money movement across the entire enterprise.
• Exceptional Communication: You can distill complex concepts into easily understood product strategy and requirements, tailoring your message to engineering, data science, and business stakeholders.
• Strong Ownership: A proactive bias for ownership, capable of taking initiative on product outcomes, finding scrappy ways around roadblocks, and driving multiple key results.

Nice to Have

• Experience tuning specific detection systems (like Oscilar, Datavisor, Flowable, or internal decision engines).
• Direct experience with the unique risk challenges of physical Check fraud and irreversible real-time payments.
• Experience working closely with Data Science and Machine Learning Engineers to operationalize real-time scoring and transaction monitoring models.