Plaid
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Data Scientist - Fraud
role at
Plaid
About Plaid Plaid builds tools and experiences that enable developers to connect financial accounts to apps and services. By 2013, Plaid had built a network covering 12,000 financial institutions across the US, Canada, UK, and Europe, powering solutions for companies such as Venmo, SoFi, and several Fortune 500 banks.
Job Overview As a Data Scientist on Plaid’s Fraud Data team, you will analyze customer and network traffic, build dashboards, run backtests, and design data models to help the team understand how our Protect product performs across segments. You will also partner with Product, Engineering, and go‑to‑market teams to design experiments, shape customer‑facing features, and support sales motions.
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.
Compensation & Benefits Base salary: $162,000 – $222,000 per year. Compensation varies by geographic zone and role.
Zone 1
– New York City and San Francisco Bay Area
Zone 2
– Los Angeles, Seattle, Washington D.C.
Zone 3
– Austin, Boston, Denver, Houston, Portland, Sacramento, San Diego
Zone 4
– Raleigh‑Durham and all other US cities
Additional compensation may include equity and/or commission. Plaid provides a comprehensive benefit plan with medical, dental, vision, and 401(k) options.
EEO Statement 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, gender, sexual orientation, age, military or veteran status, disability, or other legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need assistance due to a disability, please let us know at
[email protected] .
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Data Scientist - Fraud
role at
Plaid
About Plaid Plaid builds tools and experiences that enable developers to connect financial accounts to apps and services. By 2013, Plaid had built a network covering 12,000 financial institutions across the US, Canada, UK, and Europe, powering solutions for companies such as Venmo, SoFi, and several Fortune 500 banks.
Job Overview As a Data Scientist on Plaid’s Fraud Data team, you will analyze customer and network traffic, build dashboards, run backtests, and design data models to help the team understand how our Protect product performs across segments. You will also partner with Product, Engineering, and go‑to‑market teams to design experiments, shape customer‑facing features, and support sales motions.
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.
Compensation & Benefits Base salary: $162,000 – $222,000 per year. Compensation varies by geographic zone and role.
Zone 1
– New York City and San Francisco Bay Area
Zone 2
– Los Angeles, Seattle, Washington D.C.
Zone 3
– Austin, Boston, Denver, Houston, Portland, Sacramento, San Diego
Zone 4
– Raleigh‑Durham and all other US cities
Additional compensation may include equity and/or commission. Plaid provides a comprehensive benefit plan with medical, dental, vision, and 401(k) options.
EEO Statement 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, gender, sexual orientation, age, military or veteran status, disability, or other legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need assistance due to a disability, please let us know at
[email protected] .
#J-18808-Ljbffr