Job Description:
• Develop automated reports, dashboards, and insights across the full credit lifecycle.
• Support underwriting, risk management, portfolio monitoring, and credit performance.
• Build credit risk dashboards, reports, and analytics using Python and Tableau.
• Analyze the credit lifecycle (underwriting, performance, delinquency, and collections).
• 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 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.
Benefits:
• Flexible Time Off: 20 Days