AI & Data Scientist

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. This position requires on-site presence at our Stockholm or Gothenburg office.

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!