Team Lead Data Scientist

The Team Lead Data Scientist will oversee the data science team, leading initiatives to develop and implement advanced machine learning models with some of the use cases tailored for the telecommunications sector. This role will ensure the delivery of the data science use cases as per plan with a supporting data stack by closely communicating with the data engineering team through providing end-to-end technical expertise. The role involves collaborating with various departments and stakeholders to leverage data for strategic decision-making.

Key Responsibilities :

1.      Lead and mentor a team of data scientists and engineers.

2.      Work closely with the data engineering team to design, build, and maintain scalable data pipelines and IT environments for data storage, processing, and retrieval to support data science activities.

3.      Lead the data science team to Develop and implement machine learning models for predictive and prescriptive analytics in telecom using tools such as Python, SQL, and Dataiku.

4.      Develop and implement data models and architecture to support data use cases.

5.      Work closely with the data engineering team to Support extracting, transforming, and loading (ETL) data from various sources into data warehouses, ensuring data quality and integrity to be aware of the complete use case implementation cycle.

6.      Work closely with the data engineering team to Optimize data pipelines, queries, and processes to improve performance and efficiency.

7.      Identify and resolve data-related issues, providing technical support and ensuring the reliability and availability of data systems.

8.      Collaborate with teams, including data scientists, AI, and other stakeholders, to understand data requirements and deliver solutions that meet business needs.

9.      Evaluate new technologies and tools, integrating them into existing data infrastructure to enhance capabilities and meet evolving business requirements.

10.  Stay updated with the latest developments in data science, techniques, and best practices.

Qualifications :

• Master’s preferred in Data Science, Statistics, Computer Science, or a related field.
• At least 5 years of hands-on experience in data science, with a comprehensive understanding of data management principles.
• Proven track record in architecting and delivering robust data platforms, showcasing expertise in designing scalable and efficient solutions.
• Knowledge of CRISP-DM methodology.

Skills :

Preferred Qualifications :