Data Science Lead Main Purpose Collaborate with data scientists and business stakeholders to design, develop, and maintain efficient data pipelines feeding into the organization's data lake. Ensure the data lake contains accurate, up-to-date, and high-quality data, enabling data scientists to develop insightful analytics and business stakeholders to make well-informed decisions. Utilize expertise in data engineering and cloud technologies to contribute to the overall success of the organization by providing the necessary data infrastructure and fostering a data-driven culture.

Demonstrate a strong architectural sense in defining data models, leveraging the Poly-base concept to optimize data storage and access. Facilitate seamless data integration and management across the organization, ensuring a robust and scalable data architecture. Take responsibility for defining and designing the data catalogue, effectively modelling all data within the organization, to enable efficient data discovery, access, and management for various stakeholders.

KEY RESPONSIBILITIES: Work with stakeholders across the organization to identify high-impact opportunities for leveraging data to drive business solutions and growth. Design, develop, and implement advanced analytics models and machine learning algorithms to extract valuable insights from data.



Champion the adoption of data-driven decision-making processes throughout the organization by effectively communicating results and insights to stakeholders.

Take ownership of the end-to-end data science process, from problem statement to solution delivery, collaborating with other teams as necessary. Stay current on trends and best practices in data science, and actively promote the use of advanced analytics techniques within the organization.

Requirements: Experience 10 years of overall experience & at least 5 years of relevant experience Understanding of a multi domain (retail, B2B etc.) OTC process is a plus.

Skills Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Economics, or a related field. Robust experience with data manipulation, analysis, and visualization tools such as R, Python &

- Tableau. Knowledge of machine learning, statistical modelling, and big data platforms (e.g., Hadoop, Spark). Familiarity with cloud platforms like AWS, Google Cloud, or Azure is a plus.

Experience with ETL tools such as SSIS, Xceptor &

- Alteryx Experience in using available ML models in Azure &
- AWS Excellent attention to detail, problem solving and analytical abilities Languages: Fluency in verbal and written English mandatory Fluency is Spanish &
- French is useful.

Key Relationships: Internal: CEO &

- COO of Africa, Managers across various departments, Senior Management, Head of Departments in other regional hubs of Puma Energy External: External Consultants Experience Level Senior Level

📌 Lead - Data Science and Analytics (Mumbai)
🏢 PUMA Sports india
📍 Mumbai