Senior Manager - Analytics - Modelling - Financial Services/Banking Domain (4-10 yrs)
Senior Manager - Analytics - Modelling - Financial Services/Banking Domain
Description for Pricing, Lending, Targeting and Affordability Roles:
- We are looking for a strong candidate with 6-8 years of analytics experience in Financial Services or Banking domain to fill multiple advanced analytics positions for financial services clients.
- We are looking for a highly analytical person who will be able to extract value out of data, perform statistical analysis, build models and deliver analytical solutions using SAS, Python, Hive, Tableau and SQL.
- Strong experience on modelling projects in banking industry
- Knowledge of Credit Cards, Deposits and Loans Products.
- Expert in SAS/Python, Tableau, Hive and SQL
- Understanding of Risk Metrics like Bad Rates and Expected Loss/Balance metrics.
- Have good exposure to testing frameworks and experimentation
- Knowledge of statistical and machine learning (Probability theory, parametric and non-parametric models, supervised and unsupervised ML techniques, etc.)
- Data manipulation, extraction of data from huge / complex databases using SAS (SAS hands-on experience is a must, should be an expert in data management, SAS etc.).
Problem solving skills: Professional Experience (At least 1 of below Mandatory) - At least 6 years of hands on experience in financial services analytics.
- Experience of at least 1 working implementation of pricing analytics optimization for Loans / Deposits Products.
- Experience working with analytical use-cases of a bank's lending and saving products pricing optimization.
- Understanding of affordability metrics like Adjusted income, affordable income, monthly essential expenditure models and assigning of corresponding limits (Affordable limits, final limits) to credit products.
- Experience of developing at least 1 implementation of proactive Credit Line Increase /Credit Line Decrease Models for a Bank.
- Experience of campaign analytics, association analysis, factor analysis, customer Lifetime Value Models, Cross-sell; up sell models. Experience working with CRM data and customer segmentation models.
Tools & Platforms:
- SAS, SQL, Tableau, Python, Hadoop (Big Data), Hive
Education: Any UG/PG/Doctorate Degree in B.Sc. in Maths, B.Tech /B.E. in Computers, BCA in Computers/ Degree in Mathematics / Information Technology / Computer Applications / Engineering from a B Tech / B.E in Information Technology / Information Systems / Computer Applications
Job Responsibilities (Not limited to):
- Utilize statistical and machine learning techniques to solve challenging business problems
- Interface with clients to understand business requirements and translate them into analytical problems that can be addressed using analytical techniques
- Excellent in problem-solving skills and able to work on open ended problems
- Deliver with limited direction, usually within a complex environment, to drive rigorous, fact-based solutions and insights for clients
- Articulate and document project requirements and client meetings
- Communicate project results in the client's business context
- Seek client feedback after each delivery and learn and apply insights on subsequent projects