Summary: Manage the data science lifecycle, analyze internal data for business insights, develop models to enhance revenue, and explore data monetization initiatives. Highlights: 1. Manage the end-to-end data science lifecycle 2. Develop descriptive, predictive, and optimization models 3. Work closely with commercial teams to recommend data-based solutions **Job Description** 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. **Required Skills****Require Skills** 1\. Bachelor’s in computer science / data science / IT / Engineering 2\. 6\+ years of experience in Data Science, Machine Learning and Big Data Analytics 3\. Strong ability to clean, prepare, and work with data using SQL and big\-data tools such as Hive, Impala \& Spark. Python experience will be a plus. 4\. Hands\-on Experience in training, testing and deploying machine learning models. 5\. Experience building AI applications using LLMs is a plus. 6\. Ability to present data insights in a clear and simple way using Tableau or other data visualization tools. 7\. Good analytical thinking and the ability to understand what the data is saying from a business point of view. 8\. Experience of working as part of business team or direct engagement with business team 9\. Preferred experience working with telecom data and understanding of key telecom commercial metrics.