What You Will Do
- Build scorecards using ML algorithms (e.g. Random Forest, Gradient Boosting, XGBoost, Deep Learning) related to Credit Risk, Fraud Risk, Chance of Approval, Portfolio Management, etc.
- Closely coordinate with other functions such as Product, Technology, and Risk and align on business and technical needs
- Identify optimization/automation opportunities in the model development process such as Documentation, Turnaround Time (TAT), etc.
- Liaise with Data and Systems teams to deploy ML solutions quickly and accurately
- Participate in strategic initiatives to build in-house analytics capabilities for the platform
What You Possess
- Bachelors or any other educational qualification in disciplines such as Computer Science, Statistics, Economics, Mathematics, Business Administration, etc.
- 4+ years of working experience in data analytics, e.g. Data Processing, Feature Engineering, Model Development / Validation, Scorecard Implementation and / or Strategy formulation
- At least 1-2 years of hands-on experience of model development using tools such as R, Python, SQL, etc.
- Strong analytical and logical skills with emphasis on relating ML insights with business intuition
- Ability to take project ownership and innovate as and when required
- Domain expertise in Risk Management and / or Credit Lending domain is preferred
- A ‘detail obsessed’ professional who puts customer experience at the heart of any product design
- A technology enthusiast who is up-to-date with the latest developments in the world of technology
- Someone who can:
- Balance customer delight, technology viability and business feasibility
- Think big and take ownership of deliverables from ideation to execution
- Embrace chaos, uncertainty and volatility
- Work in a dynamic environment with a diverse set of stakeholders