We are seeking a highly analytical Data Scientist with strong proficiency in Python and R to lead a dynamic team in delivering high-impact risk solutions. You will be responsible for analyzing loss trends, simulating risk decisioning strategies, and building risk scorecards. This role requires an analytical mindset, strong problem-solving skills, and the ability to collaborate with various stakeholders to drive the implementation of risk strategies.

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.

Data Scientist

Data Scientist/ AI/ML Manager

Data Scientist - Python/R