Data Scientist, Fraud

Plaid

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
New York, NYSeattle, WASan Francisco, CA
Salary
$176,400–$226,800 / yr
Posted
49 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $172k
This role $202k
$109k $239k
below market most similar roles pay here above market

This role pays more than 73% of similar roles. Most pay $133,049–$211,611 — the blue band above. At the midpoint, this role pays about $202k versus about $172k 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 71 open roles on FindRole.

Listed pay typically runs $190,800–$262,800 across 71 roles with salary data.

Most-posted roles

View all roles at Plaid

At a glance

TL;DR · Data Scientist, Fraud

As a Data Scientist - Fraud, you will join the Fraud Data team to help build machine learning systems that identify and prevent fraud before it happens. You will analyze customer and network traffic to evaluate how Plaid Protect performs across various use cases and customer segments. Your daily responsibilities include building dashboards and metrics to provide a shared view of product performance, running backtests to identify high-impact rules and model strategies, and designing scalable data models and schemas. You will also partner with Product and Engineering to design and analyze experiments for new customer-facing features. To succeed, you must possess strong proficiency in SQL and Python, along with experience in product analytics, experimentation, backtesting methodologies, and translating complex analyses into actionable insights.

What does a Data Scientist earn in New York?

Median $173200 from 46 postings across 20 companies.

See salary data

What you'll do

  • Analyze customer and network traffic to evaluate fraud detection performance across various use cases.
  • Build dashboards and metrics to provide a shared view of product performance.
  • Run backtests to evaluate model performance and identify high-impact rules or strategies.
  • Generate data-driven insights to support customer growth and product expansion.
  • Design scalable data models and schemas to enable reliable analysis and reporting.
  • Partner with Product and Engineering teams to design and analyze experiments for new features.
  • Own the metrics and experiments that inform overall product strategy and decision-making.

What we're looking for

  • 3–5 years of relevant experience.
  • At least 2–3 years of experience working extensively with product analytics, experimentation, or data-driven products.
  • Strong proficiency in SQL and Python to analyze complex datasets and translate insights into action.
  • Hands-on experience with product analytics, experimentation, and/or backtesting methodologies.
  • Experience building and maintaining dashboards, reporting frameworks, and core product metrics.
  • Strong communication and stakeholder management skills to translate complex analyses for technical and non-technical audiences.
  • Experience in fraud/risk domains (preferred).
  • Experience with developing ML models (preferred).

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