Data Scientist - Fraud at Plaid

New York, New York, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Fintech, Financial ServicesIndustries

Requirements

3–5 years of total experience, including at least 2–3 years working deeply with product analytics, experimentation, or data-driven products
Strong proficiency in SQL and Python
Hands-on experience with product analytics, experimentation frameworks, or backtesting methodologies
Skilled in designing, building, and maintaining dashboards and core product performance metrics
Capable of designing and interpreting backtests or offline evaluations for ML and rules-based systems
Excellent communicator with strong stakeholder-management skills across diverse teams
Background in fraud or risk domains (nice to have)
Familiarity with data-insights products and a solid understanding of model-performance metrics (nice to have)
Exposure to customer-facing or GTM-facing analytics (nice to have)

Responsibilities

Work at the intersection of product analytics, machine learning, and fraud/risk to drive meaningful product improvements
Own the metrics, dashboards, and experimentation frameworks that inform product strategy and decision-making
Analyze complex datasets to uncover clear, actionable insights that shape product direction
Partner with go-to-market teams to demonstrate the technical and business value of our products to customers
Analyze customer and network traffic to understand how Protect performs across different segments and use cases
Build dashboards and performance metrics that create a clear, shared view of product health for both the team and our go-to-market partners
Run backtests on customer traffic to evaluate model and rule performance, uncover high-value opportunities, and generate insights that support sales motions and customer expansion
Design the underlying data models and schemas that enable efficient, reliable analysis and reporting
In close partnership with Product and Engineering, help design and evaluate experiments that shape new customer-facing features and inform the future of our fraud products

Skills

Key technologies and capabilities for this role

Machine LearningFraud DetectionData AnalysisDashboardingPerformance MetricsBacktestingData ModelingSQLPythonExperiment DesignFeature EngineeringModel TrainingModel DeploymentMonitoring

Questions & Answers

Common questions about this position

Is this position open to remote workers?

Yes, Plaid is open to remote candidates for this role.

What are the required skills for this Data Scientist role?

Candidates need 3–5 years of total experience including 2–3 years in product analytics, experimentation, or data-driven products, strong proficiency in SQL and Python, hands-on experience with product analytics, experimentation frameworks, or backtesting, and skills in designing dashboards and metrics plus backtests for ML.

What is the salary or compensation for this position?

This information is not specified in the job description.

What does the Fraud Data team at Plaid do?

The Data team within Plaid’s Fraud organization builds machine learning systems for fraud detection products, managing the full lifecycle from feature development to deployment and monitoring, while analyzing traffic, building dashboards, running backtests, and partnering with Product and Engineering.

What experience makes a strong candidate for this role?

Strong candidates will have 3–5 years of experience with at least 2–3 years in product analytics, experimentation, or data-driven products, plus proficiency in SQL/Python and hands-on work with dashboards, metrics, and ML backtesting.

Plaid

Connects financial accounts to apps securely

About Plaid

Plaid simplifies financial data management for individuals and businesses by connecting various financial accounts to apps and services. Its main product is a set of APIs that allow developers to integrate financial data into their applications, enabling users to track spending, initiate payments, and access financial services all in one place. Plaid serves a wide range of clients, including app developers and financial institutions, and is used by popular apps like LendingTree and Square. Unlike many competitors, Plaid focuses on providing a comprehensive and scalable platform that supports various financial use cases, such as transactions and identity verification. The company's goal is to enhance the way users interact with their financial data, making it easier and more secure.

San Francisco, CaliforniaHeadquarters

2013Year Founded

$714.3MTotal Funding

SERIES_DCompany Stage

Fintech, Financial ServicesIndustries

1,001-5,000Employees

Benefits

We've got you covered: From medical, life, and 401ks, we’re here to support your physical, mental, and financial wellbeing.

Everyone is an owner: We want everyone to feel ownership over their work - literally, which is why we offer equity to full-time Plaids.

Vacation your way: We want to make sure you have time to meet your personal needs with unlimited PTO and two weeks of synchronous, company-wide vacation.

Grow your skills: Every Plaid is in control of their career development with our learning stipends, tools, and trainings.

Risks

Increased competition from API-based banking solutions like FIS's Code Connect platform.

Potential legal challenges, such as PNC's lawsuit over trademark issues.

Demand for enhanced transparency and security in financial data sharing.

Differentiation

Plaid offers seamless financial data integration through robust APIs for diverse clients.

Plaid's Pay by Bank for Bill Pay provides a cost-effective recurring payment solution.

Plaid's strategic partnerships enhance its value proposition in payroll and payment sectors.

Upsides

Plaid's expansion into the Triangle area indicates growth and increased hiring potential.

Partnership with Dwolla enhances Plaid's presence in the secure payments sector.

Collaboration with Ansa expands market reach through pay-by-bank capabilities for merchants.

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