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Fraud Solutions Consultant

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Plaid

Plaid is a financial technology company providing APIs and network connectivity for businesses to build financial products. Its platform supports bank-account linking, financial data access, identity verification, fraud and risk tools, credit underwriting, and bank payments.

Series D8 current maintainers7 active leads1 new active lead2 lead step-downsTeam intelligence

Maintainer signals as of 8/14/2026

Distributed

Funding history

About Plaid

Plaid operates a financial data network and API platform that lets businesses connect to financial institutions and build financial experiences. Its products support account and identity verification, real-time balance and transaction data, investment and liability data, income and underwriting workflows, fraud and AML risk checks, and multi-rail bank payments. It serves developers, businesses, financial institutions, platforms, lenders, banks, and consumer-facing financial-product providers.

View jobs by Plaid

Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will own fraud retrospectives and proof-of-concept programs from end to end. You will work with customers and internal stakeholders, explain the return on investment of fraud products, recommend implementations, convert retrospective results into production usage, and relay customer feedback to product teams.

Requirements

  • 5-10 years in a customer-facing analytical role in fintech, financial services, software, or technology
  • Experience working closely with data science teams
  • Experience managing consultative customer engagements
  • Ability to interpret machine learning model output
  • Ability to explain model output to non-technical audiences
  • Data science or ML engineering background
  • Fraud, identity, or risk experience

Responsibilities

  • Own the retrospective and proof-of-concept process end to end
  • Collaborate with customers and internal stakeholders
  • Help customers understand the return on investment of Protect
  • Recommend implementations of fraud products
  • Drive follow-through to convert retrospective results into production usage
  • Serve as a feedback loop between customers and product teams

Benefits

  • Equity
  • Medical insurance
  • Dental insurance
  • Vision insurance
  • 401(k)