AVP - Collection Analytics - BFS

About the Collection Analytics Team:

- Collection Analytics is a data science team within the Retail Analytics arm . The team manages end-to-end analytical support to Collection Function of Retail Assets (both Secured and Unsecured products). Analytical support includes:

- Data Science - Developing, maintaining, evaluation ML based statistical models to predict customer's propensity to pay, to bounce, and other drivers to aid Collection

- Collection Strategy: Effectively deploying the models to augment Collection efforts; evaluating past strategies and continue to better then for higher impact

- Ad-hocs Analysis: Jointly work with business stakeholder to identify and understand business problems, generate hypothesis and solve it using data

About the Role (AVP - Collection Analytics) :

- This is a team lead role where in the individual is required to work closely with senior leaders to augment Collection efforts, and demonstrate the value proposition of analytics.

Core Responsibilities of the Role :

- Develop, maintain, and monitor Collection models

- Design or ideate newer analytical methods / frameworks which monitors the value-add of current analytical output and suggests weaker spots to improve Collection Models / Strategy

- Design, and deploy Collection outreach strategy using model output to effectively increase Collection Contact Rate and Payments

- Effectively communicate the analytical output to stakeholders

Job Requirements :

- 8-10 years of work experience in similar role; preferably in BFSI/Consulting domains

- Proficient with Python, R, SQL, SAS, other equivalent analytical tools

- Should have deep understanding of latest statistical tools for developing machine learning models and other statistical models like decision tree, CART, Logistic Regression, Linear Regression

- Should able to build strong data centric analytical framework for performing periodic reviews of delinquency, model performance, and Collection Strategies

- Should have good understanding of Retail Asset Products in Banking i.e. Housing Loans, Credit Cards, Loan Against Properties, Personal Loans.

- Should have strong written & verbal communication skills

- Experience with data visualization tools, such as Power BI , Tablue etc. would be a plus

- Educational Qualifications : MBA, M.Sc (Maths, Stats, Economics), M. Tech , B. Tech from top trier Colleges

- Hands on experience in developing application scorecards, collections models, propensity models would be a plus