Vice President - Analytics - KPO

VP-Analytics

Lead - Collections Analytics, would cover all the products in Retail Lending (Cards, Retail loan, SBB, Rural lending) and will play a key role in shaping up the strategies across collections stages. He/She would be responsible for end to end strategy, design/development and performance synthesis of Collections

Key Responsibilities :

The candidate will be responsible for the following in his/her job role :

- Lead a 20-25member team of analysts for Collections Analytics

- Design and own collection strategies

- Strategy design would involve advanced statistical modelling techniques including AI/ML

- Track the performance of the strategies and evolve continuously with test & learn framework

- Drive frameworks/ models to lower Entry rates/flow into Delinquency and towards higher resolutions (& mix) in collections buckets

- Budget and forecast NPA/Provision additions/write off recovery

- Manage stakeholders and guide them on the right strategic approaches

- Joint ownership of key metrics along with the business team

- Sustainability - initialization of models/ strategies by compete automation with the help of automation/data engineering team

- Create and maintain the foundational data infrastructure that is critical for the success of analytical work

Qualifications : Degree (master's or above) in a quantitative subject such as Engineering, Operations Research, Statistics, Economics or Finance

Role Proficiencies :

Profile of Ideal Candidate :

1) 8+ years of relevant experience in the financial services domain and/ or analytics functions. Track record of increasing responsibility and success in leadership roles

2) Sharp analytical thinker. Well-versed in dealing with numbers and large quantities of data. Proven thought leader

3) Having a 'results oriented' attitude with 'go get it done' skill

4) Experience with using data profiling tools to query data, identify anomalies, gaps and issues

5) Experience with SAS, R, and Python for data analysis and data management activities

6) Experience working with data in various forms: files (Excel, csv.), relational databases, data warehouses, unstructured data environments