Fraud Strategist

Plaid

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: New York, NY
Salary: $181,200–$294,000 / yr
Posted: 161 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $173k

This role $238k

$111k most similar roles pay here $314k

This role pays more than 86% of similar roles. Most pay $142,487–$202,591 — the shaded band above. At the midpoint, this role pays about $238k versus about $173k 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 70 open roles on FindRole.

Listed pay typically runs $190,800–$262,800 across 70 roles with salary data.

Most-posted roles

View all roles at Plaid

At a glance

TL;DR · Fraud Strategist

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The Fraud Strategist joins the Fraud team to build and mature the retro-as-a-service and POC program while driving adoption of fraud products. This role serves as a critical bridge between the data team and customers, requiring the ability to interpret machine learning model outputs, such as precision, recall, and score distributions, to present compelling business cases to non-technical audiences. Day-to-day responsibilities include managing end-to-end retro processes, partnering with customers to determine return on investment for fraud products, and providing a feedback loop to the product team to influence the roadmap. The role requires expertise in consultative customer engagement and analytical experience within fintech or financial services. The work focuses on leveraging transaction patterns, device signals, and behavioral data to solve the specific business problem of detecting and preventing fraud using financial network data.

Skills

Data Science ML Engineering Fraud Prevention Precision Recall Score Distributions

What you'll do

Manage the retro-as-a-service and proof-of-concept programs from start to finish.
Partner with customers to identify ROI and recommend specific fraud product implementations.
Convert retro results into active production usage through consistent follow-through.
Translate complex machine learning model outputs into clear business cases for non-technical audiences.
Act as a feedback loop between customers and the product team to influence the roadmap.
Manage consultative customer engagements while owning both the deliverables and the relationship.

What we're looking for

5-10 years of experience in a customer-facing analytical role in fintech, financial services, or a related domain.
Experience working closely with data science teams.
Experience managing consultative customer engagements where you owned the deliverable and the relationship.
Comfort interpreting ML model output and explaining it to a non-technical audience.
Background in data science or ML engineering, particularly on a fraud or risk team (preferred).
Experience in fraud, identity, or risk from a vendor, bank, fintech, or consulting engagement (preferred).

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