Payment Risk Strategist

Plaid

United States

On-site

USD 120,000 - 190,000

Full time

3 days ago
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Benefits offered by this job

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Job summary

Plaid is seeking a Payments Risk Strategist to support Signal and Guarantee, interpreting model outputs and diagnosing performance to drive threshold and rules recommendations. You will own proofs of concept and retros, improving integrations and scaling processes across risk products.

You will proactively optimize Signal customers, read model outputs, and partner with AEs and TAMs to deliver data-driven risk insights. This role combines analytics with customer-facing engagements.

Qualifications

  • Experience interpreting risk, decisioning, or quantitative model outputs.
  • Ability to diagnose performance problems and recommend data-backed thresholds.
  • Comfortable pulling and analyzing data with SQL.

Responsibilities

  • Interpret model outputs to diagnose drivers of authorization and return-rate performance.
  • Own proofs of concept and retros and turn analysis into actionable recommendations.
  • Optimize Signal customers by prioritizing accounts with higher return rates.
  • Read model outputs and recommend threshold and rule changes aligning with customer risk goals.
  • Help Guarantee customers tune thresholds to protect loss performance.
  • Partner with AEs and TAMs to bring deep product and modeling expertise into customer engagements.
  • Improve decision and return reporting to strengthen customer experience and Plaid models.
  • Turn recurring insights into onboarding playbooks and product requirements.

Job description

  • Our Payments Risk team builds and operates decisioning capabilities across Signal and Guarantee. We help customers tune thresholds and rules so they can approve more good transactions while reducing returns. For Guarantee, this work also protects the economics of the risk Plaid underwrites
  • You will be the technical, customer-facing Payment Risk Strategist for Signal and Guarantee. You will interpret model outputs, diagnose customer performance, and turn that analysis into concrete threshold and rules recommendations. You will own proofs of concept and retros, improve existing integrations, and help the team identify patterns that can be scaled through better processes and product capabilities
  • Own customer proofs of concept and retros from analysis through recommendations and follow-through
  • Proactively optimize Signal customers, prioritizing accounts with high return rates
  • Read model outputs and diagnose the drivers of authorization and return-rate performance
  • Recommend threshold and rules changes that align with each customer’s risk and authorization goals
  • Help Guarantee customers tune thresholds to achieve target authorization rates while protecting loss performance
  • Partner with AEs and TAMs to bring deep product and modeling expertise into customer engagements
  • Improve decision and return reporting from customers to strengthen their experience and Plaid’s models
  • Turn recurring customer insights into onboarding playbooks and product requirements
Benefits
  • Vibrant offices in SF, NYC, and Raleigh-Durham—with catered meals, happy hours, and clubs to keep you connected
  • Competitive pay, comprehensive health benefits, and support for fertility, mental health, and parental leave
  • Lifestyle perks including home office stipends, daycare support, and commuting benefits like CitiBike and Lyft

Experience interpreting risk, decisioning, or other quantitative model outputs[Nice to have] Familiarity with cash flow or bank transaction data5–10 years of experienceExperience diagnosing performance problems and making data-backed threshold or rules recommendationsExperience partnering across go-to-market and technical teamsComfortable pulling and cutting your own data (SQL)[Nice to hold] Experience at a fraud or risk-scoring vendor, credit bureau, or bank / processor risk teamDemonstrated ability to build repeatable processes in an ambiguous environmentStrong customer-facing consulting and communication skills

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