Plaid operates a financial data network and API platform that lets businesses connect to financial institutions and build financial experiences. Its products support account and identity verification, real-time balance and transaction data, investment and liability data, income and underwriting workflows, fraud and AML risk checks, and multi-rail bank payments. It serves developers, businesses, financial institutions, platforms, lenders, banks, and consumer-facing financial-product providers.

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Skills

Airflow Analytics Causal Inference Communication Dashboarding Data Modeling Data-Pipeline Data Science Dbt Experimentation Fintech Machine-Learning Okr Python Sql

Candidate Availability

Hybrid · San Francisco · Required

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

Become a data and analytical thought partner to product managers and engineers as Guard launches and scales from 0 to 1. Translate business questions into analytics projects, perform strategic analysis, improve visibility through data modeling and dashboarding, create OKRs and metrics, support feature decisions through experimentation, and influence prioritization and execution.

Requirements

5-8+ years of experience as a Data Scientist or in a related analytics or data-focused role
Fintech experience, including working with raw fintech data
Experience launching direct-to-consumer products from 0 to 1
Experience with experimentation, ad-hoc analysis, and strategic insights
Strong SQL skills and experience creating metrics that drive stakeholder alignment
Experience building or partnering on Airflow and dbt data pipelines
Strong communication and cross-functional partnership skills
Experience driving data-driven performance for user-facing products
Track record of influencing top-line OKRs, prioritization, roadmapping, or execution
Nice to have: causal inference, machine learning, and Python proficiency

Responsibilities

Champion data-first decision-making as Guard is built and scaled.
Serve as a data and analytical thought partner to product managers, engineers, and cross-functional stakeholders.
Translate ambiguous business and product questions into analytics projects and decision frameworks.
Perform ad-hoc and strategic analyses to improve user outcomes and business performance.
Build and maintain data models, dashboards, metrics, and OKRs.
Design and analyze experiments supporting feature launches and iterations.
Partner on Airflow- and dbt-powered data pipelines.
Identify ways to impact top-line OKRs and influence prioritization, roadmapping, and execution.
Explore machine learning prototypes and causal inference approaches where useful.

Benefits

Medical, dental, and vision insurance
401(k)
Equity