Some careers open more doors than others.
Retail Banking and Wealth Management (RBWM) serves more than 50 million customers worldwide with a complete range of banking and wealth management services to enable them to manage their finances and protect and build their financial futures. It is a global business that brings together management responsibility for Retail Banking, Wealth Management, Insurance and Asset Management with a focus on customer-centric propositions and innovative and efficient distribution channels.
The role of Insights Analyst is responsible for identifying and driving increased revenue generation for Retail Banking products and propositions by industrialising customer and product analytics. You will work closely with the Analytics & CRM Manager, as well as marketing teams to incorporate customer insights and activities to support brand strategy. Furthermore you will monitor and assess portfolio performance, providing recommendations on campaigns and analytical methodologies.
***Please note: this role will be a fixed term contract until August 2019***
To be successful in this role, you will need:
- Interface and collaborate with local, regional and global business partners to identify business opportunities and challenges, and transform them into analytics projects.
- Design, formulate, and implement relevant solutions in the form of actionable data-driven insights that will lead to achieving business goals (revenue growth, retention, and increasing customer engagement, etc.).
- Closely collaborate with relevant teams/stakeholders to obtain the support required.
- Use statistical and data mining software/tools to extract, collect, manipulate raw data to prepare for further analysis. You will then be required to apply the appropriate analytics frameworks, statistic procedures or machine learning algorithms to analyse the data in order to provide actionable insights.
- Interpret and present quantitative information as well as the findings in proper context so as to help in the investigations and decision making of the business
- To design and develop robust, relevant data mining solutions (descriptive or predictive)
- Apply diverse modelling methods including (but not limited to): decision tree, clustering, logistic regression, gradient boosting, neural network, random forest, support vector machine etc.
- Manage the timely delivery of output and effectively communicate with all stakeholders