AI & Data Scientist
Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Sep 22, 2026. Capgemini scores B on the Alion truth index.
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 collaborate with clients to understand complex business challenges and turn data into measurable business value. You will design, develop, and validate AI, machine learning, and advanced analytics solutions.
At Capgemini, we believe great Data Scientists combine analytical rigour with business understanding and technological curiosity. You may work with forecasting customer demand, optimising industrial operations, building recommendation engines, or assessing whether an AI use case is feasible.
You will help clients make evidence-based decisions by applying statistical modelling, machine learning, data visualisation, Generative AI, and advanced analytics.
In this role you will play a key role in:
- Data Wrangling & Analytics: work with data wrangling, advanced analytics, statistical modelling, machine learning, and data visualisation to uncover insights and support better decisions. Use tools such as Matplotlib, Seaborn, Power BI, and Qlik.
- Use Case Assessment & Experimentation: run AI use case assessments and feasibility analyses. Frame business problems as analytical questions and design experiments to test assumptions and evaluate potential value.
- Predictive Analytics & Optimisation: build forecasting, recommendation, optimisation, predictive maintenance, and decision-support solutions.
- Model Validation: validate models for performance, robustness, drift, and explainability. Apply experimental design, A/B testing, and uncertainty quantification when evaluating models and analytical results.
- Generative AI & Agentic AI: apply Generative AI, Large Language Models, AI agents, and frameworks such as LangChain, LangGraph, and LlamaIndex where they create tangible business value and complement traditional Data Science approaches.
- Data Platforms & Cloud: work with modern data platforms such as Databricks, Snowflake, Azure Data Lake, Azure Synapse, Spark, and cloud-native analytics environments across Azure, AWS, and Google Cloud.
- Client Collaboration: partner closely with stakeholders to translate business problems into analytical solutions. Explain models and analytical results clearly to business stakeholders and ensure that solutions align with the EU AI Act and GDPR.
- Deployment & Knowledge Transfer: package models for deployment using APIs and REST services, document the solutions, and transfer knowledge to the client team.
Your profile
- Experience as a Data Scientist, Analytics Consultant, or similar, with an interest in Generative AI, Agentic AI, AI agents, orchestration frameworks, intelligent automation, and AI copilots.
- Experience with LLMs (GPT, Claude, Gemini, Kimi, or similar) and frameworks such as LangChain, LangGraph, and LlamaIndex.
- Experience with Python (including Pandas, Polars, NumPy, Scikit-learn, PyTorch, TensorFlow, Spark, PySpark) or R.
- Strong SQL, database experience, and knowledge of statistical methods including experimental design, A/B testing, and uncertainty quantification.
- Experience with analytics and visualization tools such as Matplotlib, Seaborn, Power BI, and Qlik.
- Knowledge of cloud analytics platforms, APIs, REST services, and Git version control.
- Ability to explain analytical models and results to business stakeholders and identify opportunities to create business value through analytics.
- Degree in Mathematics, Statistics, Engineering, Computer Science, IT, or a related quantitative field, and fluent English.
If you also have experience with Databricks, MLOps, knowledge graphs (Neo4j), Kubernetes, Docker, and speaks Swedish fluent that's even better!
What we believe you will enjoy about working here
- The opportunity to shape your own development, whether you want to deepen your expertise in Data & AI or explore new roles and areas of responsibility.
- A culture where learning is part of everyday work - through certifications, communities, knowledge hubs, and colleagues who are always willing to share their knowledge.
- Flexibility in how and where you work, with opportunities for hybrid working when assignments allow.
Application
As part of our recruitment process, identity verification will be conducted through inspection of your ID card, and background checks may be carried out as required. We welcome applicants with different backgrounds and experiences. If you're excited about this role but don’t meet every requirement, we encourage you to apply anyway.
We believe diverse perspectives make better products and stronger teams. We actively strive to create an inclusive environment where everyone feels valued and empowered to contribute. We welcome applicants of all genders, backgrounds, and experiences.
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About Capgemini
Capgemini is the business transformation partner for enterprises in the age of AI. We help organizations imagine and build an intelligent, sustainable future, combining AI, technology and human ingenuity to transform how they operate, innovate and grow. With unique end-to-end capabilities spanning strategy, technology, engineering and intelligent operations, we bring together deep industry expertise and market-leading capabilities in AI, cloud and data to turn ambition into measurable business outcomes at scale. Supported by a robust ecosystem of partners and nearly 60 years of expertise, Capgemini is a responsible and diverse global organization of over 410,000 team members in more than 50 countries. The Group reported 2025 revenues of €22.5 billion.
Make it real | www.capgemini.com