AVP - Decision Analytics - Bank

AVP - Decision Analytics

HIRING FOR A UK BASED BANK.

LOCATION- NOIDA

Introduction:

Deliver hypothesis-driven analysis to investigate key business issues relating to Bank's customers, markets, products and channels, and use this insight to drive the wider Retail and Business Bank's agenda to create value for customers, colleagues, the community and the company

What will you be doing?

- Identify performance trends, customer behaviours and commercial opportunities and risks through application of quantitative analytical skills

- Undertake analysis to understand customer behaviour, product and financial performance to then help to maximise product

performance, support product plans and drive key strategic initiatives with support from senior analytics colleagues.

- Contribute to the design, test and build of complex information across multiple decision engines to identify causal links between customer behaviour and business opportunities and performance

- Demonstrate an innovative approach to data-based problem solving, and have input into the development of an analytic strategy that supports business strategy and also develops a strong working relationship with teams.

- Take part in initiatives to improve the accuracy, availability, granularity and coverage of our data, and those that implement new data management and manipulation tools.

- Communicate the findings of analysis in meetings with senior stakeholders and in visually-compelling reports or presentations.

What we're looking for:

- Experience in creating business models, both financial and consumer behavioural

- Experience in using innovative customer analysis to identify commercial opportunities

- Experience of programming in SQL, and in additional computer languages (e.g. SAS, R, Python) desirable.

Skills that will help you in the role:

- Experience of statistical analysis techniques desirable

- Practical experience of creating customer segmentation models, and running customer targeting

- Practical knowledge of data warehouse and MI environments and practices.