Business Analytics – Liabilities

Roles and Responsibilities Identifying and prioritizing business use cases : Work with business heads / product heads to identify and prioritize business problems which can be solved through data analytics. The individual should have knowledge of Retail Banking Liabilities (Savings, Current Accounts, Deposits), Investment and Insurance products (Mutual Funds, Life Insurance, Broking) Opportunities identification : Identify incremental cross-sell and deepening opportunities in the existing customer base of retail bank. Identifying opportunities for increasing relationship value of customer, revenue per customer, driving primary banker penetration and cross-sell ratio. Building the analytics engine : Lead a team of business analysts, who have knowledge of SQL / SAS & / or R / Python and can draw insights from customer demographic data, banking transactions and product usage. Experience of having built credit / propensity / classification models individually or jointly with the data science team. Guiding the data scientist : Liaise with data scientists to build propensity models or advanced ML / DL solutions based on the problem statement Business Understanding and Stakeholder Management : Deep understanding of liabilities / RM managed customer segments. Drive implementation of analytics solutions jointly with business owners. Strong Analytical Skills : Expertise in using statistical tools SAS / R / Python. Ability to generate business insights from data Strategic Analytics : Ability to holistically understand a business problem, break it down to logical components, laying the analytics framework and leading the team to build meaningful insights around it