Job description:

Long Description Job Summary

Insight generation by building data mining and statistical models to support Customer Value Management (CVM) and Loyalty Programs by translating model outputs into actionable insights for business units

Job Responsibilities

Data Mining & Advanced Analytics model development

• Actively use built-in data analytics models on CDP, including customer segmentation, churn prediction, propensity modelling and next-best activity; continuous update and adjustment of model parameters and performance tracking of the models on CDP
• Build advanced predictive analytics models offline by using programming languages such as R, Python, SQL and implement those models to CDP to generate them; score the model in other tools and integrate the results to CDP if the model is too complex to be generated on CDP; leveraging infrastructure including Cloud computing solutions and relational database environments
• Stay on top of changing conditions by retraining and testing the model regularly; enhance it whenever necessary
• Monitor models’ accuracy to catch any degradation in its performance over time
• Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand user interactions

Insight generation

• Actively seek and identify where data science can provide value to business areas across the BUs, provide solutions to BUs analytical problems and validate the solution performance
• Generate actionable insights and predictive modeling techniques to modify consumer behavior

Reporting

• Active use of built-in reporting tools on CDP; day to day report generation and maintenance using BI tools and be involved in any new tool selection and deployment
• Engage with stakeholders to ensure that data insights are effectively communicated through the most appropriate data visualization and navigation tools

Candidate Requirements

• University Degree
• Background in Applied Math, Statistics, Physics, Engineering, or Computer Science; Advanced degree strongly preferred
• 3+ years of experience with data science and statistical analysis in a business, marketing
• Examples of domain expertise of interest are: predictive modeling, churn analysis, time series forecasting, computer vision, text mining, recommender systems, market basket analysis, segmentation, graph analytics with strong programming skills in Python or R
• Experience with dashboard and reporting tools such as Tableau and Qlik
• Ability to explain and discuss mathematical and machine learning technicalities to a business audience

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