Actionable (4-6)
- 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
Key Skills
- 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
