Axis Bank - Manager - Model Development - Rural Lending

Model Development - Rural Lending

Job Description

1. Candidate will lead rural lending team. Responsibility of this team is to deliver best in class risk models across all rural lending products across customer lifecycle. The candidate would be responsible to drive these modeling projects, covering all aspects of the model development process (liaising with stakeholders, understanding businesses need/requirement, the creation of model design, exhaustive data prep, building a robust model, implementation, and regular monitoring).

2. In addition to that, candidate will also be required to:

- Challenge the status quo, introduce new methodology to improve power and efficiency of models

- Be able to find out and explore new data sources

- Standardize and automate processes wrt implementation & monitoring, as much as possible

Key Result Areas

1. Managing a team of 1-2 modelers, and deliver robust risk models that generates tangible business value, using statistical modeling techniques adhering to model development guidelines

2. Work very closely with data team, IT team, credit policy and product analytics team for any model implementation / underwriting process change projects

3. Standardization & automation of manual & repetitive processes

4. Bring innovation on to the table by trying newer modeling methods to improve model accuracy

5. Ensure flawless delivery of projects on time

6. Ensure people are motivated and their training and learning needs are met

Competencies Required

- Technical skills: Statistical model development / Predictive Analytics

- Soft Skills: Leadership, Interpersonal, Communication skills

- Should have high level of motivation and be a fast learner

Academic Qualifications Required

- Post graduation in Statistics or Economics or Quantitative Economics OR

- M.B.A. (Finance / Quantitative Methods)

Nature of Relevant Work Experience Required Statistical model development using different machine learning techniques. Should have developed models using logistic and linear regression. Having worked on Artificial Neural Network, Random Forest, SVM, Stochastic Gradient Boosting, Bayesian methods etc. is a plus.

Must have worked on SAS, R