# Senior Data Scientist - Network Value

**Company:** [Plaid](https://hotfix.jobs/companies/plaid)
**Location:** San Francisco, CA, New York, NY, Seattle, WA
**Role:** Data Science
**Salary:** $191k – $263k/yr
**Experience:** 5+ years
**Skills:** SQL, Airflow, dbt, Python, Machine Learning, Causal Inference, Experimentation, Data Modeling, Dashboarding, Analytics
**Posted:** 2026-05-15

> Data Scientist embedded in product teams, partnering with PMs and engineers to drive data-informed decisions for a critical user-facing fintech product through analysis, experimentation, modeling, and ML prototypes.

## Job Description

## Responsibilities
- Champion a data-first approach toward decision-making across the entire organization
- Become the data and analytical thought partner to product managers and engineers
- Translate business questions into analytics projects
- Perform ad-hoc and strategic analyses to identify opportunities for improved outcomes and support business decisions
- Build data models and dashboards to improve visibility into core systems
- Create OKRs quantifying progress against business goals
- Design and analyze experiments to support feature ship decisions
- Build ML prototypes and causal inference models

## Qualifications
- 5-8+ years of experience as a Data Scientist or in a related analytics or data-focused role
- Experience with experimentation, ad-hoc analysis, and developing strategic insights
- Strong SQL skills and experience creating metrics that drive alignment with stakeholders
- Experience building data pipelines with Airflow and dbt
- Strong communication skills and experience partnering cross-functionally with product managers, engineers, and other stakeholders
- Experience driving data-driven performance for user-facing products
- Track record of identifying novel ways to impact a top-line OKR and influencing stakeholders on prioritization, roadmapping, and/or execution

## Nice to Have
- Fintech experience and experience working with raw fintech data
- Experience with causal inference, machine learning, and Python

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