Senior Manager - Analytics - Modelling - Financial Services/Banking Domain

Job 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.

Key competencies

- 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.

Pricing:

- 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.

Affordability:

- 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.

Limits:

- Experience of developing at least 1 implementation of proactive Credit Line Increase /Credit Line Decrease Models for a Bank.

Targeting

- 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 and 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.