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Product Manager, Fraud Data

Build Protect's signal stack with data scientists

Develop and improve Protect's fraud signal with data team, creating attributes and scores for real-time customer decisions, owning feature roadmap and labeling pipeline

Why This Role?

Work on building the largest network of trusted identities in the US

Key Responsibilities

  • Own feature roadmap for Protect, including validation and measurement
  • Build and manage labeling pipeline as a product
  • Define product requirements for fraud vector scores
  • Partner with data scientists to translate model needs into product requirements

Requirements

  • Fraud expertise
  • Data science knowledge
  • Ability to partner with data scientists
  • Understanding of model needs and product requirements

Required Skills

product managementfraud detectiondata sciencemachine learningdata infrastructureData analysisCommunicationCollaboration

Keywords

fraud detectiondata scienceproduct managementfinancial servicesidentity verification
View Original Description from Ashby Job Boards

Original description from Ashby Job Boards

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, Washington D.C., London and Amsterdam. The Fraud team is building the largest network of trusted identities in the US. Our products span the full user lifecycle: Identity Verification and Monitor for onboarding and compliance, Layer for frictionless returning-user experiences, and Protect, our fraud intelligence platform, as the connective risk layer for all of it. Protect has more inbound demand than any product we have launched. The challenge is signal. We are building the data infrastructure that will make Protect the best fraud signal in financial services. This is a product role for someone who lives at the intersection of fraud expertise and data science. You will work directly with our data team to build and improve Protect's signal stack: the attributes, scores, and fraud vector intelligence that customers use to make real-time decisions. You need to understand fraud, know how to partner with data scientists as a peer, and be able to translate between what models need and what products should deliver. Responsibilities: - Own the feature roadmap for Protect: what we build, how we validate it, and how we measure coverage and fill rates - Build and manage the labeling pipeline as a product, including customer retros, data partnerships, and the label feedback loop into model training - Define the product requirements for fraud vector scores, including signal selection, precision/recall targets, and customer-facing output design - Partner with data scientists and MLEs as a day-to-day collaborator, not just a requester. Translate between model needs and product requirements in both directions - Work with GTM and Protect PM on how attribute improvements and new scores translate into customer-facing value propositions. Qualifications: - Required: - Real hands-on fraud prevention experience: fraud vectors, detection systems, risk signal evaluation. Not general fintech. - Direct experience collaborating with data scientists or ML engineers to ship data-driven products. You need to be able to talk to a DS about feature distributions, label quality, and model performance, not just read summaries. - Nice to have: - Experience at a fraud vendor (SentiLink, Sardine, Socure, Persona, Incode) or a fraud operations team at a large fintech or bank - Background with ML model inputs/outputs: feature engineering, offline evaluation, and moving from experimentation to production - Specialization in a specific fraud vector (ATO, synthetic identity, or first-party fraud) 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 https://plaid.com/legal/#candidate-privacy-notice. 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.

Salary Context

Similar Data & Analytics roles on LokerDollar pay around $200k/yr (range $41.6k–999k/yr, n=61 active listings).

Hiring at Plaid

Plaid has 57 other active roles on LokerDollar and has been hiring here since May 7, 2026 — across Data & Analytics, Engineering, Product, Marketing.

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Company
Plaid
Source
Ashby Job Boards
Salary
See remote (USD) vs local pay →
Job Type
full time
Location
Remote
Seniority
senior
Posted
Jun 23, 2026

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Frequently asked questions

Is Product Manager, Fraud Data at Plaid a remote job?
This role is based in Remote. See the listing for remote/onsite details.
What is the salary for Product Manager, Fraud Data at Plaid?
The listed pay range for this role is $190.8k–262.8k/yr.
What type of employment is Product Manager, Fraud Data at Plaid?
This is a full time position.
How do I apply?
Click the "Apply" button on this page to go to the official application at Plaid.

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