Data Scientist - Fraud

Engineering

San Francisco

Full-time

We build simple yet innovative consumer products and developer APIs that shape how everybody interacts with money and the financial system.

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.

The Data team within Plaid’s Fraud organization builds the machine learning systems that power Plaid’s newest fraud detection products, leveraging the breadth of Plaid’s network data to stop fraud before it occurs. We manage the full lifecycle of these systems—from feature pipeline development and model training to deployment, serving, and monitoring—ensuring our solutions scale reliably as we grow to support hundreds of customers.

As a Data Scientist on Plaid’s Fraud Data team, you will analyze customer and network traffic to understand how Protect performs across different segments and use cases. You’ll build dashboards and performance metrics that create a clear, shared view of product health for both the team and our go-to-market partners. You will 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. You’ll also design the underlying data models and schemas that enable efficient, reliable analysis and reporting. In close partnership with Product and Engineering, you will help design and evaluate experiments that shape new customer-facing features and inform the future of our fraud products.

***We are open to remote candidates***

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.

Qualifications

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.

$176,400.00 - $243,600.00 per year

The target base salary for this position ranges from $176,400/year to $243,600/year [in Zone 1, in Zone 4 or encompassing all Zones]. The target base salary will vary based on the job's location.

Our geographic zones are as follows:

Zone 1 - San Francisco / New York City / Seattle

Zone 2 - Los Angeles / Washington DC / Austin / Boston / Sacramento / San Diego

Zone 3 - Atlanta / Portland / Chicago / Philadelphia / Denver / Miami / Dallas / Raleigh

Zone 4 - All other US cities

The base salary range listed for this full-time position excludes commission (if applicable), equity and benefits. The pay range shown on each job posting is the minimum and maximum target for new-hire salaries. Actual pay may be higher or lower depending on factors like skills, experience, and relevant education or training.

Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!

Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.

Please review our Candidate Privacy Notice here.

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