Payment Risk Strategist
AI in this role
A Payment Risk Strategist at Plaid is responsible for interpreting quantitative model outputs and recommending threshold adjustments for risk decisioning products.
We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam.
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.
Responsibilities
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.
Qualifications
5–10 years of experience
Comfortable pulling and cutting your own data (SQL)
Experience interpreting risk, decisioning, or other quantitative model outputs.
Experience diagnosing performance problems and making data-backed threshold or rules recommendations.
Strong customer-facing consulting and communication skills.
Experience partnering across go-to-market and technical teams.
Demonstrated ability to build repeatable processes in an ambiguous environment.
[Nice to have] Experience at a fraud or risk-scoring vendor, credit bureau, or bank / processor risk team.
[Nice to have] Familiarity with cash flow or bank transaction data.
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.
Please review our Candidate Privacy Notice here.
Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.
How we score this
Payment Risk Strategist at Plaid scores 0 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.
AI Level 1. The work itself involves no AI, or AI only appears as scenery, such as a company tagline.
- AI Level 480 to 100
- AI Level 360 to 79
- AI Level 240 to 59
- AI Level 10 to 39
Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where risk analysis was part of your work. What did you do?
- Tell me about a project where data analysis was part of your work. What did you do?
- Tell me about a project where decision modeling was part of your work. What did you do?
- What's a project where you used Sql hands-on?
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- List these exact terms on your resume: Risk Analysis, Data Analysis, Decision Modeling, and Sql. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
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