Senior Scientist - Risk Analytics - BFS - IIT/IIM/MDI/FMS

The role of Senior Analytics Scientist - Risk Analytics is based in Noida and reports to the Sr. Mgr / Director leading the team.

Position - Sr. Analytics Scientist - Risk analytics (R/SAS/Machine Learning / Python / SQL)

Location - Noida

Key responsibilities include-

The key requirement for the role is the ability to understand the business, develop data driven solutions to address business problems and provide analytic support to the risk analytics group. The individual will possess the ability to work in teams and display a proactive learning attitude.

- Building models to predict risk and other key metrics

- Coming up with data driven solutions to control risk

- Finding opportunities to acquire more customers by modifying/optimizing existing rules

- Doing periodic upgrades of the underwriting strategy based on business requirements

- Evaluating 3rd party solutions for predicting/controlling risk of the portfolio

- Running periodic controlled tests to optimize underwriting

- Monitoring key portfolio metrics and take data driven actions based on the performance

- Business Knowledge: Develop an understanding of the domain/function. Manage business process (es) in the work area. The individual is expected to develop domain expertise in his/her work area.

- Teamwork: Develop cross site relationships to enhance leverage of ideas. Set and manage partner expectations. Drive implementation of projects with Engineering team while partnering seamlessly with cross site team members.

- Communication: Responsibly perform end to end project communication across the various levels in the organization.

Requirement :

Preferred :

- 2- 7 years of experience in Financial Services/Analytics Industry/eCommerce

- Understanding of the financial services business

- Bachelor / Masters from tier 1 institutes.

Skills :

- Should have solid understanding of probability and stats; Bayesian methods, probability distributions, Central limit theorem etc.

- Should be familiar with some of the following GLM, logistic regression, Random forest, Gradient boosting trees, CART, Na- ve bayes, Linear Program, Mixed Integer program, etc.

- Hands on experience of analytical tools such as R / Python / Machine learning