As a Data Scientist, you will play a key role in developing end-to-end solutions for AI use cases. By taking up a use case right from the start you will help business define and scope the problem, pick the right AI solution and technology as well as ensure implementation, integration and deployment of your solution to production. You will do so while ensuring that our internal governance processes and best practices are respected. You will also collaborate with other team members in knowledge sharing as well as continuously improving our way of working.
Mission context
- Develop AI applications using state-of-the-art Gen AI technology.
- Translate business requests into AI applications.
- Deploy prototypes to production, with support of IT, to obtain reliable, scalable systems.
- Identify high-value use cases through data exploration and visualization.
- Pilot prototypes in production processes to demonstrate their value.
- Present your results in a clear manner and discuss them with multi-functional project teams.
- Work in close collaboration with business experts (e.g. for requirement gathering, data source identification, data and process understanding, feature engineering, result validation, etc.), with IT (e.g. for ETL, deployment to production, etc.) and with other Data Scientists in the team (e.g. for knowledge sharing).
Degree & experience:
- PhD or Master's degree in a quantitative field (Artificial Intelligence, Computer Science, Engineering, Statistics, Mathematics, etc.)
- 3-5 years of relevant work experience in a business environment
Technical profile requirements
- Strong coding skills in Python, with proficiency in software development best practices, including Version Control (e.g., GIT) and DevOps (e.g., CI/CD pipelines).
- Experience with Microsoft Azure and Azure AI Services.
- Experience with Langchain and/or Langgraph for creating AI Agents and Generative AI flows.
- Strong knowledge of state-of-the-art AI and statistical methods.
- Proven proficiency in the end-to-end AI project life cycle, including:
- Translating business requests into data requirements
- Identifying high-value use cases through data exploration and visualization
- Developing AI solutions (incl. feature engineering, model fitting, etc.)
- Deploying scalable AI applications to production.
Attitudes/behavior
- Passionate about AI and a constant learner
- Result-oriented and highly proficient in transforming data into actionable insights that create business value
- Strong collaboration and communication skills, with experience working alongside a diverse team of technical and non-technical stakeholders.
- Able to manage AI projects in an autonomous way and drive collaboration with domain experts, data engineers and other AI engineers
- Knowledge in the field of telecommunications is a plus
