Data Scientist - Manager
Indexed description
challenging problems across different industries. We are on a mission to transform the world, and you will be instrumental in shaping how we do it with your ideas, thoughts, and
solutions
Qualifications
Responsibilities
- Partner with product and business teams to understand challenges, identify
measurable value
- Evaluate and select the most suitable AI approaches, including LLMs, RAG systems,
- Design and build machine learning pipelines, from experimentation and prototyping
- Develop, fine-tune, and optimize AI models (including LLMs and generative AI
- Set up and maintain AI/ML development and production infrastructure, leveraging
- Build robust data ingestion, transformation, and feature engineering pipelines to
- Identify and curate high-value training datasets, leverage transfer learning, and
- Create APIs, integrations, and tools that enable stakeholders to operationalize AI
- Help stakeholders understand AI outcomes, limitations, and trade-offs, ensuring
- Continuously research and recommend emerging AI capabilities (LLMs, multimodal
Qualifications
- Strong experience designing, developing, and deploying AI/ML products or
- Strong programming skills in Python
- Solid experience with data manipulation and ML tooling: NumPy, Pandas, scikit learn, etc
- Proven experience building and fine-tuning models with TensorFlow, PyTorch, Keras
- Hands-on experience with LLMs, RAG systems and vector databases
- Familiarity with NLP, generative AI, prompt engineering, embeddings, and
- Strong understanding of data science methodology, applied statistics, ML/DL, and
- Experience with MLOps and cloud-native development: Docker, Kubernetes, CI/CD,
- Practical experience with cloud AI platforms
- Strong algorithmic and problem-solving skills, with the ability to deliver end-to-end
- German speaking (C1 at least)
- Consulting background; Background in the Energy and Commodities or Financial Services sector is a plus
- Experience defining AI or data strategies for organizations
- Hands-on experience with modern AI tools (e.g., generative AI, copilots, automation platforms)
- Exposure to data architecture, data engineering, or product development
- Track record of driving AI adoption or innovation initiatives within organizations
- Advanced degree in a relevant field (e.g., data science, engineering, business, or similar)
We’re looking for someone who is:
- Equally comfortable in the boardroom and with a dataset
- A translator between business ambition and technical reality
- Curious, adaptable, and excited about the fast-moving AI landscape
- Motivated to go beyond pure data science into broader problem-solving and innovation
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