Data Scientist Lead

Capgemini is a global business and technology transformation partner with nearly 60 years of heritage, employing 420,000 team members in more than 50 countries. The Group reported 2024 global revenues of €22.1 billion. Its Group IT function supports and partners with the business to implement global IT standards, integrates business units into a unified IT services model, and delivers technology initiatives that maintain security and improve working efficiency.

• 12+ years of experience in data science with a Master's or PhD degree from a Tier 1 institute
• Strong experience developing and deploying AI/ML, Generative AI, and Agentic AI models in production
• Strong knowledge of machine learning, deep learning, NLP, statistical analysis, and data visualization tools and technologies
• Experience with big data processing frameworks such as Spark or Hadoop
• Extensive experience with deep learning frameworks such as TensorFlow, PyTorch, and Keras
• Strong expertise in NLP techniques and tools, including experience with LLMs like Gemini, GPT, BERT, etc.
• Proficiency in programming languages such as Python, R
• Experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services; preference for GCP
• Experience with MLOps practices and tools for continuous integration and deployment of machine learning models
• Strong leadership and team management skills with experience leading data science teams
• Excellent communication and collaboration skills to work with cross-functional teams and stakeholders
• Strong data security and privacy knowledge and experience
• Experience with agile development methodologies is a plus

• Drive the strategic vision for AI/ML initiatives and contribute to the overall AI strategy of the company
• Communicate complex technical concepts and results to business stakeholders effectively
• Provide thought leadership and subject matter expertise in data science
• Collaborate with cross-functional teams to understand business needs and translate them into data science solutions
• Lead a team of data scientists, MLOps engineers, ML engineers, and solution architects, providing guidance, mentorship, and coaching
• Oversee the end-to-end lifecycle of multiple AI/ML projects, from data collection and preprocessing to model training, evaluation, and deployment
• Leverage Agentic AI, Generative AI, and large language models (LLMs) to create innovative applications and solutions
• Design, develop, and implement data science projects including machine learning models, deep learning models, Agentic and Generative AI, NLP solutions, statistical analysis, and data visualization
• Ensure data quality, scalability, and reliability of AI systems
• Stay up to date with the latest data science trends and technologies
• Contribute to the development of data-driven solutions and products
• Present data science generated insights and recommendations to stakeholders