Data Scientist
Description
At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.
Job Description
You will be joining a global team of passionate data professionals working at the cutting edge of machine learning, AI, and GenAI innovation. At Capgemini Engineering, we believe in turning data into decisions — building models that don't just sit in notebooks, but drive real business outcomes at scale. If you are ready to work on meaningful problems, with the freedom to innovate and the support to grow, this is the place for you.
Your Role
In this role you will play a key role in:
- Designing, building, and deploying machine learning models including forecasting, classification, and propensity models that deliver measurable business impact in production environments.
- Developing and maintaining scalable data pipelines using PySpark and cloud platforms such as Azure, Databricks, or equivalent, ensuring efficient data processing across large datasets.
- Building and shipping GenAI-powered products including RAG pipelines, vector search systems, and agentic workflows using LLM APIs at scale for real-world applications.
- Writing complex, high-performance SQL and Python code to extract, transform, and analyse data, supporting robust and reproducible analytical workflows.
- Communicating model insights and results clearly to non-technical stakeholders using tools like SHAP, translating complex outputs into actionable business recommendations.
Your Profile
- 4+ years of hands-on experience with Python and SQL, including complex joins, CTEs, window functions, and query performance tuning, applied in professional or production-level environments.
- Proven experience delivering production-grade ML models using frameworks such as XGBoost and/or LightGBM, with a track record of real forecasting, classification, or lead scoring work.
- Demonstrated hands-on experience building GenAI products — including RAG systems, vector search, and tool-use agents — as well as working with LLM APIs at scale for tasks such as data labelling or metadata extraction.
- Experience working with cloud and data platforms such as Azure and/or Databricks, with GCP/Vertex or AWS/SageMaker also considered.
- Strong ability to collaborate across teams, communicate technical findings to diverse audiences, and contribute to a culture of curiosity, experimentation, and continuous improvement.
What you'll love about working here
Free access to learning platforms – Free access for all to world-class learning assets and curated programs from Harvard Business Review, Coursera, Pluralsight, Udemy, Microsoft, AWS, Google and many more.
Well-being Hub – The global Well-Being Hub connects employees across various facets of well-being: work-life balance, working hours and network growth.
FlexAbroad – Employees in 20+ countries can work abroad for up to 45 days in a 12-month period.
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Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.