Data Scientist - Python/R

Data Scientist

Roles & 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 and drive the implementation of risk strategies.
• Manage challenging time constraints to ensure on-time delivery of projects.
• Work closely with partner teams in identifying, evaluating, and recommending 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 and recommend credit risk decisioning and model deployment strategy.
• Build a risk scorecard that leverages both internal and external performance data for credit decisioning.
• Collate analysis and build presentations that help articulate the risk strategy for the leadership team.

Skills Required:

• Experience in analyzing data and using database query language (e.g.,

  SQL

  ).
• Proficiency in programming and developer tools such as

  Python, R

  , and

  Databricks

  in a finance or analytics field.
• Experience in leading high-performing teams of analysts.
• Experience in working with non-traditional data such as social media will be 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; and 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.

QUALIFICATION:

• Quantitative background in engineering, statistics, math, economics, business, or related disciplines.