Data Science Manager, Fraud

Plaid

Confirmed live today High trust

Quick summary

Work type
On-site
Location
New York, NYSeattle, WASan Francisco, CA
Salary
$216,000–$329,400 / yr
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $196k
This role $273k
$140k most similar roles pay here $350k

This role pays more than 95% of similar roles. Most pay $160,300–$231,100 — the shaded band above. At the midpoint, this role pays about $273k versus about $196k for comparable roles.

Based on 240 similar postings.

Employer

About Plaid

Plaid is a financial technology company that builds a data network powering digital finance applications, enabling consumers to securely connect their financial accounts to apps and services. Industry: Financial Technology & Data Infrastructure

Plaid currently has 41 open roles on FindRole.

Listed pay typically runs $201,600–$272,400 across 41 roles with salary data.

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View all roles at Plaid

At a glance

TL;DR · Data Science Manager, Fraud

Data Science Manager - Fraud will lead a team within the Fraud Data organization focused on customer-facing data science and product analytics. The manager is responsible for setting the team roadmap, mentoring data scientists, and overseeing technical reviews while remaining hands-on with critical investigations. Key responsibilities include defining product metrics, establishing processes for customer retrospectives, identifying recurring fraud signals, and translating customer insights into scalable product capabilities. This role requires deep expertise in fraud and risk domains to improve and scale fraud products. The ideal candidate possesses strong technical skills in Python, SQL, statistics, and applied modeling. Additional preferred experience includes graph-based data systems, causal inference techniques, model interpretability, and dbt for data transformation. The work centers on solving complex fraud problems by building robust data foundations and analytics to drive product decisions.

What you'll do

  • Establish a 6–12-month roadmap for fraud product analytics in collaboration with Product, Engineering, and GTM teams.
  • Define product metrics, data foundations, and reporting practices to guide investment decisions and measure product health.
  • Create repeatable processes for customer retrospectives and proofs of concept to turn insights into scalable features.
  • Identify recurring fraud signals and work with engineers to develop them into automated product capabilities.
  • Review analytical designs, data models, code, and model evaluations while performing hands-on technical investigations.
  • Manage and coach a team of data scientists through performance discussions and professional development opportunities.
  • Translate complex customer insights and fraud analyses into actionable growth opportunities for go-to-market teams.

What we're looking for

  • Proven experience managing, mentoring, and developing high-performing data scientists.
  • Deep domain expertise in fraud, risk, or related areas.
  • Strong experience in product analytics, metric design, and measuring product performance.
  • Experience partnering directly with customers to deliver data-driven insights and solutions.
  • Strong technical depth in Python, SQL, statistics, product analytics, and applied modeling.
  • Demonstrated ability to set technical direction and deliver complex initiatives while remaining hands-on.
  • Excellent communication and cross-functional collaboration skills across Product, Engineering, Machine Learning, and GTM teams.
  • Experience with graph-based data, causal inference, model interpretability, or dbt (preferred).

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