Data scientist

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Your Role

As a Data Scientist, you will be responsible for designing, developing, and deploying machine learning and Generative AI solutions that drive business outcomes. You will leverage advanced analytics, predictive modeling, and large language models to deliver intelligent automation, decision support, and operational optimization across various domains.

• Design, develop, and deploy Machine Learning models for prediction, forecasting, anomaly detection, classification, and optimization.
• Build AI-driven solutions for Root Cause Analysis (RCA), event correlation, risk scoring, and operational intelligence.
• Develop predictive maintenance and intelligent recommendation systems.
• Create Generative AI applications using LLMs, Retrieval-Augmented Generation (RAG), and prompt engineering techniques.
• Develop AI-powered virtual assistants, knowledge discovery systems, and troubleshooting solutions.
• Perform data exploration, feature engineering, statistical analysis, model evaluation, and performance tuning.
• Translate business requirements into scalable AI, ML, and analytics solutions.
• Collaborate with Data Engineers, Solution Architects, Subject Matter Experts, and business stakeholders to deliver end-to-end AI initiatives.
• Ensure deployed models are scalable, reliable, and production ready.

Your Profile

• Strong programming expertise in Python and SQL with 6- 14th Years of Experience
• Experience with JavaScript, React, or Angular (preferred for AI application development).
• Strong knowledge of Machine Learning, Predictive Analytics, Time-Series Forecasting, Anomaly Detection, and Classification Models.
• Hands-on experience with Generative AI, including:
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)
  • LLM Guardrails
  • MCP Servers / Agent Tool Layer
• Experience with cloud platforms such as AWS and Amazon SageMaker.
• Expertise in Data Modeling, Feature Engineering, Data Visualization, and Statistical Analysis.
• Strong analytical, problem-solving, and communication skills.
• Experience with LangChain and AI orchestration frameworks.
• Knowledge of MLOps / LLMOps practices and deployment pipelines.
• Exposure to Predictive Maintenance solutions.
• Experience in Industrial IoT Analytics.
• Knowledge of Network Analytics and Operational Technology (OT) Analytics.
• Familiarity with enterprise-scale AI solution deployment and monitoring.

What you'll love about working here