Data Scientist - Python/R

Key Responsibilities:

• Team Leadership: Lead and mentor a high-performing team of risk analysts focused on credit risk initiatives.
• Cross-functional Collaboration: Partner with product managers, engineers, and data scientists to build relationships and implement end-to-end risk solutions.
• Project Management: Ensure timely delivery of critical risk-related projects, managing competing deadlines and priorities effectively.
• Data Strategy: Identify, evaluate, and recommend alternative data sources to enhance credit differentiation and segmentation.
• Analytics & Strategy Simulation: Analyze portfolio trends, simulate credit strategies, and deliver insights that drive optimization of approval rates, losses, and profitability.
• Model Deployment Alignment: Work with the data science team on credit model decisioning and deployment strategies.
• Scorecard Development: Build and refine risk scorecards using internal and external performance data for both underwriting and account management use cases.
• Executive Communication: Prepare presentations and analytical summaries to communicate risk strategies and performance metrics to leadership.
• Continuous Improvement: Constantly refine strategies through iteration, testing, and integration of new insights.

Ideal Candidate Profile:

• Education: Bachelor's or Master's degree in a quantitative field such as Statistics, Economics, Engineering, Mathematics, or Business.
• Experience:
• 5+ years of experience in credit risk analysis, financial analytics, or a related field.
• 2+ years of experience in leading a team of analysts.
• Experience working with large datasets, SQL, Python, R, and platforms like Databricks.
• Experience with model development or supporting model deployment is a plus.
• Data & Tools Proficiency:
• Strong knowledge of data manipulation, query languages (SQL), and programming for analysis (Python/R).
• Familiarity with analytics platforms and BI tools.
• Exposure to non-traditional data (e.g., social media, behavioral) is a plus.
• Soft Skills:
• Strong analytical thinking and problem-solving skills.
• Excellent communication and storytelling skills for both technical and non-technical audiences.
• Ability to thrive in a fast-paced, dynamic environment with a high level of ambiguity.
• Strong interpersonal skills to work effectively across teams and levels.
• Proactive mindset and ability to take ownership of risk issues.

Nice to Have:

• Prior experience in credit model building or governance.
• Exposure to consumer lending, credit cards, or BNPL (Buy Now, Pay Later) products.
• Experience working in a regulated financial services or fintech environment.