Data Scientist - Credit (Retros)

Plaid • New York, NY

3d • $176,400 - $226,800

About The Position

As a Data Scientist on Plaid’s Credit team, you’ll apply quantitative analysis and deep credit expertise to help lenders make better use of cash flow insights. You’ll work across customer problems, credit policy, and data products, translating Plaid’s data into recommendations and insights that drive business impact and inform product direction.

The role involves analyzing model performance for clients, investigating issues and improvement opportunities, identifying credit risk signals in Plaid data, and building and evaluating credit retrospectives. You’ll create customer-specific recommendations, develop and maintain data pipelines, and build metrics, alerts, and dashboards for monitoring production machine learning models. You’ll also own the development of recommendations for using cash flow insights in lending decisions, support customer adoption of Plaid Insights, serve as a credit insights and policy subject matter expert, and inform Product and Engineering through clear analysis and presentations.

Requirements

• 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 and how to optimize marketing, acquisition, customer management, and collections or recoveries.
• Demonstrated ability to make data-driven decisions.

Nice To Haves

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

Responsibilities

• Deep-dive into model performance for clients, triage issues, and identify opportunities to improve outcomes.
• Analyze Plaid data to identify emerging credit risk signals and build and evaluate credit retrospectives.
• Create tailored recommendations for clients based on their data and Plaid’s insights.
• Build and maintain data pipelines, including ETL processes.
• Develop metrics, alerts, and dashboards to monitor production machine learning model performance.
• Develop hands-on recommendations for incorporating cash flow insights into lending decisions using account-level decisioning best practices.
• Improve customer adoption of Plaid Insights through customer-specific analysis.
• Serve as a subject matter expert on credit insights and credit policy implementation, supporting Data Science, Engineering, and Go-to-Market partners.
• Apply quantitative analysis, data mining, and data visualization to develop models and actionable insights.
• Identify useful signals that can inform machine learning models.
• Inform and influence Product and Engineering teams through clear analysis and presentations.

Benefits

• Medical benefits.
• Dental insurance.
• Vision insurance.
• 401(k).
• Equity and/or commission may be provided as additional compensation, depending on the position offered.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed