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.
We are looking for a Data Science Specialist to join a product-focused engineering team. In this role, you will work closely with data scientists, ML engineers, and domain experts to analyze complex datasets, understand model behavior, and drive improvements through data quality, structure, and insight-driven analysis. This position is highly hands-on and focuses on improving model performance through deep data understanding.
Data Understanding and Representation Analysis
Model-Aware Data Analysis
Data Quality and Curation
Insight-Driven Improvements
Minimum Qualifications
Master’s or PhD in Data Science, Computer Science, Applied Mathematics, Statistics, Physics, or a related field
2–3+ years of hands-on data science experience with real-world ML datasets including time-series, images, video, or sensor data
Strong proficiency in Python and core data science libraries such as NumPy, pandas, matplotlib, seaborn
Experience using dimensionality reduction and representation analysis tools such as UMAP, t-SNE, PCA
Experience analyzing data for classical ML and deep learning pipelines
Strong understanding of ML fundamentals, evaluation methods, and diagnostic techniques
Preferred Qualifications
Experience with sensor or time-series data such as magnetic, radar, 3D, environmental, or IoT data
Familiarity with scikit-learn preprocessing workflows
Experience handling imbalanced datasets, label noise, sensor noise, and data drift
Understanding of embedding analysis, feature importance, and model interpretability methods
Experience working with data annotation teams or managing labeling processes
Familiarity with MLOps or data versioning tools such as MLflow, Weights and Biases, or DVC
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.

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real | www.capgemini.com