Data Scientist - Python/R

Key Responsibilities:

• Lead a dynamic team to deliver high-impact risk solutions across credit risk (underwriting, exposure controls, and line management).
• Work with stakeholders across product management, data science, and engineering to build relationships with partner teams and drive the implementation of risk strategies.
• Manage challenging time constraints to ensure on-time delivery of projects.
• Collaborate with partner teams to identify, evaluate, and recommend new data that helps in risk differentiation.
• Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates, etc.
• Work closely with the data science team to recommend credit risk decisioning and model deployment strategies.
• Build a risk scorecard leveraging both internal performance data and external performance data for credit decisioning at underwriting and account management reviews for existing customers.
• Collate analysis and build presentations to articulate the risk strategy for the leadership team.

Position Requirements:

• Quantitative background in engineering, statistics, math, economics, business, or related disciplines.
• 5+ years of experience in analyzing data and using database query language (e.g., SQL), and programming and developer tools such as Python, R, and Databricks in a finance or analytics field.
• 2+ years of experience in leading a high-performing team of analysts.
• Experience working with non-traditional data (e.g., social media) is a big plus.
• Prior model-building experience is a plus but not critical.
• Possesses an analytical mindset and strong problem-solving skills.
• Attention to detail and ability to multitask.
• Comfortable working in a fast-paced environment and dealing with ambiguity.
• Possesses strong communication, interpersonal, and presentation skills; ability to engage and collaborate with multiple stakeholders across teams.
• Extremely proactive communicator, willing to raise flags when needed and keep team members informed of ongoing risk or fraud-related activities.