1.       Manage the Data science lifecycle from data provision to model development, evaluation, presentation, and commissioning.

2.       Analyze small and large volumes of internal data to produce meaningful insights that support business decisions.

3.       Explore internal datasets to identify potential use cases and insights that can be packaged for external partners as part of data monetization initiatives.

4.       Work closely with the Data Engineering team to develop, maintain and enhance the analytical datasets to be used for data science models.

5.       Develop descriptive, predictive, and optimization models to enhance revenue generation, reduce churn and gain operational efficiency

6.       Design and develop algorithms to generate insights from big data and to identify new data-driven products and services with working knowledge of mostly used Big Data & analytics tools e.g. Cloudera, R, Python, Hadoop, Spark

7.       Work closely with commercial teams to understand their objectives and recommend data-based solutions.

8.       Independently manage assigned tasks and projects, taking ownership from analysis through to delivery.