Senior Data Scientist - Credit Risk & Consumer Insights

Experian

About The Position

We're looking for a Senior Data Scientist with credit analytics experience to develop automated reports, dashboards, and insights across the full credit lifecycle. You'll support underwriting, risk management, portfolio monitoring, and credit performance, while partnering directly with clients to ensure analytics align with their needs. You will report to the VP of Analytics Product Build, Innovation, and Scores. You'll have opportunity to: Build credit risk dashboards, reports, and analytics using Python and Tableau. Analyze the credit lifecycle (underwriting, performance, delinquency, and collections) to identify important insights. Develop and automate reporting pipelines and monitoring frameworks. Translate analytics into strategies for risk, business, and client teams. Perform deep‑dive analyses on credit behavior, defaults, and scoring models. Present insights to clients in clear, applicable formats. Guide clients in using dashboards and analytics for decision‑making. Ensure data quality, accuracy, and compliance with reporting standards. Improve existing reporting and build new analytics for better forecasting and risk assessment. Mentor junior team members on visualization, reporting, and credit analytics. Be a trusted advisor in client meetings, presentations, and workshops.

Requirements

5+ years in credit risk analytics, data science, or BI with credit lifecycle focus.
Python skills (Pandas, NumPy, SQLAlchemy, and Matplotlib).
Proficient in Tableau dashboarding and data visualization.
Experience with credit risk metrics, loan performance, and lifecycle modeling.
Experience with large datasets and data warehouse environments.
SQL for ETL and automated reporting.
Clear communicator, able to simplify complex insights.
Client‑facing experience translating analytics into strategies.
Background in financial services, FinTech, or lending.
Experience with ML models for credit risk.
Familiarity with regulatory reporting in credit/lending.

Nice To Haves

Knowledge of Power BI or Looker.

Responsibilities

Build credit risk dashboards, reports, and analytics using Python and Tableau.
Analyze the credit lifecycle (underwriting, performance, delinquency, and collections) to identify important insights.
Develop and automate reporting pipelines and monitoring frameworks.
Translate analytics into strategies for risk, business, and client teams.
Perform deep‑dive analyses on credit behavior, defaults, and scoring models.
Present insights to clients in clear, applicable formats.
Guide clients in using dashboards and analytics for decision‑making.
Ensure data quality, accuracy, and compliance with reporting standards.
Improve existing reporting and build new analytics for better forecasting and risk assessment.
Mentor junior team members on visualization, reporting, and credit analytics.
Be a trusted advisor in client meetings, presentations, and workshops.