Description

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