VP - Analytics & Data Science/Machine Learning - BFS

Job Introduction

Exp in Asset - Credit card, Personal loan

The role holder will deliver end to end, the projects in the analytics and ML domain. He/she will collaborate with Senior RBWM Leadership team to determine and prioritize immediate requirements, and anticipate future Analytics, ML, BI/MI, Campaign, and data needs. Responsible to work on prioritized Analytics projects, handling trigger engine, employee advocacy program and critical Sr. Management/Group/Region ad-hoc requests and consulting to ensure high quality delivery of actionable insights, modelling, product , network analytics and business analysis.

Principal Responsibilities

This position would entail functional management as an individual contributor. The incumbent would be required to

a. Liaise with colleagues in INM, D&A colleagues across Region & Global and also with Region/Global business leaders to deliver impactful analytics projects.

b. Have in-depth business knowledge across a breadth of functional areas within Retail Banking

c. Be proficient in evaluating new technologies and identifying practical business application to develop enhanced business value and increase operating efficiency.

d. Provide technical/functional leadership to multiple teams and ensure execution of projects/ analysis as per the agreed timelines and with accuracy and quality from the teams.

e. Provide strategic and tactical analytics systems support across the organization

f. Interface with vendors to determine immediate information requirements, anticipate future needs towards building robust databases for future analytics

g. Manage projects/sprints and small working groups towards delivery of Proposition,Liabilities,Assets, Wealth,Customer and Risk management analytics

h. Build and deploy machine learning models for achieving high business impact

Qualifications/Requirements:

- 8 years of Analytics Experience focused preferably in the Banking & Financial Services Domain.

- Demonstrated problem solving skills in handling complex business problems with the help of analytics

- Should have extensively worked in analytics and data science domain

- Should have a practical understanding of ML models, scorecards and should have built and deployed at least 5 commercial grade models in the domain of customer analytics, risk, fraud, recommenders, marketing analytics etc.

- Knowledge and high fluidity inSQL,Python is mandatory, good handle over SAS is desirable

- Strong track record of stakeholder management across business functions

- Exceptionally strong organizational, problem-solving and communication skills