•  Scorecard Building and Modelling  

• Developing analytical models to assess risk profile of a customer / identifying cross-sell opportunities/fraud control for new and existing customers
  
  
• Responsible for development and deployment of various scorecards / models for the credit risk / Retail asset products of the Bank within the specified timelines. Ensure the deployment also is line with Bank’s strategies so as to gain maximum efficiencies.
  
  
• Estimate probability of default arising out of the scorecards and monitor deviation from expected default rates.
  
  
• Monitor portfolio and identify pockets of opportunity for business growth and risk alerts to control NPAs. Communicate these alerts to the respective owners and follow-up for closure
  
  
• Formulating data cuts and strategies to assess credit risk for new and existing customers of the Bank. Give feedback to stakeholders to improve the usage of the models
  
  
• Develop novel approaches/algorithms in Risk modeling to constantly improve the operational efficacy of current models and its impact to stake holders
  
  
• To adopt the latest trends wrt fintech companies by applying the best-in-class financial models, risk strategies
  
  
• To work on various aspects related to automation of scorecards in Analytics domain.
  
  
• Explore data available within the Banks ecosystem but not used currently to meet the above stated business objectives

• Innovation

• Thinking, evolving and making significant changes
  in the processes, techniques, methods so as to save
  time, energy and money.
  
  
• Any other assignments depending on the needs of the organization

• MCA/MTech/MSc Statistics or Economics/BTech/MBA or equivalent in Computer science/Statistics or related areas with strong inclination towards machine learning algorithms is preferred

• Excellent problem solving capabilities with strong fundamentals in computer science
  
  
• Strong technical & analytical skills
  
  
• Hands-on experience in data wrangling (ETL), feature engineering, building and deploying scalable machine learning algorithms
  
  
• Strong written and verbal communication skills
  
  
• Excellent knowledge of current trends in the field of machine learning/analytics field

Experience Required

• Experience of 2+ years in analytics/predictive modeling/machine learning
• Experience of 2+ years in Python/R in building as well as deploying scalable analytics based models
• Exposure to banking preferable

Major Stakeholders (intra team and cross functional stakeholders, who would need to be interacted with for
discharging duties)

• Credit Policy
• Underwriting
• Process
• Fraud Control
• Product
• Credit Bureaus
• Third Party Analytics Service Providers
• IT
• Legal
• Information Security