Data Scientist - Credit (Retros)

The role

You will apply quantitative analysis and credit expertise to help lenders use cash flow insights. You will work across customer problems, credit policy, and data products to drive business impact.

What you will do

• Deep-dive into model performance for clients and triage issues.
• Analyze Plaid's data to identify credit risk signals and build credit retrospectives.
• Create tailored recommendations for clients.
• Build and maintain data pipelines including ETL processes using tools such as dbt.
• Develop metrics, alerts, and dashboards to monitor machine learning model performance.
• Develop recommendations for incorporating cash flow insights into lending decisions.
• Improve customer adoption of Plaid Insights through custom analysis.
• Serve as a subject matter expert on credit insights and credit policy implementation.
• Apply expertise in quantitative analysis, data mining, and data visualization to develop models.
• Identify useful signals that can inform machine learning models.

Required qualifications

• 2–5 years of industry experience in a financial services Data Science role.
• Deep familiarity with SQL and Python.
• Deep understanding of credit risk and the development of underwriting models.
• Hands-on credit expertise building and maintaining credit policies for lenders.
• Knowledge of the lending lifecycle including marketing, acquisition, customer management, and collections or recoveries.
• Demonstrated ability to make data-driven decisions.

Nice to have

• Experience building data pipelines and automating ETL processes with dbt or similar tools.

Benefits

• Medical
• Dental
• Vision
• 401(k)

About the company

Plaid powers the tools millions of people rely on to live a healthier financial life. The company works with thousands of companies to make it easy for people to connect their financial accounts to apps and services.