Apply statistical modeling and quantitative analytic to understand customer behaviour and identify insights in providing recommendation for customer segmentation strategy, cross-sell, up-sell and customer retention
Create and continuous enhancement of predictive modelling in improving marketing campaign efficiency.
Provide ad-hoc business analyses necessary in recommending business solutions to senior management team of the company.
Assist supervisor to build and strengthen customer analytics capability for marketing applications
Identify opportunities and provide recommendations for effective business analyses and campaign execution on customer / distribution channels.
Job Responsibilities
Develop the propensity / predictive models to maximize the usage and customer response in customer up-selling / cross-selling campaigns.
Drive to develop and implement of customer analytics solution.
Monitor movements of customer segments and to continuously provide business insights that are relevant in relation to customer strategy and behaviors;
Identify and monitor customer behaviors through researches or marketing activities for deriving customer insights.
Perform in-depth customer and campaign analysis with recommendations.
Assist the supervision in the design, development and implement of customer analytics solution
Contribute ideas on enriching the existing customer data
Requirements
Bachelor's degree in Statistics, Computer Science, Mathematics or Actuarial Science with at least 8 years' relevant experience in data mining, data modeling, business/customer analytics or execution of database campaign
Demonstrated understanding / proficiency on SAS and SQL
Knowledge in SAS EM is preferred
Prior experience in financial institutions and knowledge of insurance business is preferred.
Results focused, with a track record of achievement
Strong interpersonal skill and communication skill in English
Proactive and excellent team player, and also can work independently under pressure.