Senior Data Scientist (m/f/d)

About us:

HyPlus is your companion in digital transformation. Together with our clients, we develop their digital DNA in a structured, partnership-based manner with a clear focus on sustainable added value. We support companies from requirements analysis through architecture, software development and implementation to operation. With around 800 colleagues in Germany, Poland, Lithuania, Romania, and India, we combine technological excellence with industry expertise in Automotive, Retail, Banking & Insurance, and the Public Sector.

We welcome applicants who are already working with modern AI-powered development tools and generative AI, or who are interested in integrating them meaningfully into their daily work. We see the reflected use of AI as a valuable addition to technical know-how and independent thinking.

As a Senior Data Scientist, you will be responsible for end-to-end data science solutions for our clients: from evaluating the use case, through model development and validation, to going into production. You will be the technical point of contact for statistics, machine learning, and the practical application of generative AI, translate business questions into analytical solution approaches, advise stakeholders at eye level, and share your knowledge within the team.

• Design and technical leadership of data science and AI projects in interdisciplinary teams – from problem definition to productive deployment

• Identification and evaluation of use cases regarding feasibility, data availability, and economic viability, as well as translation of business questions into analytical and technical solution approaches

• Exploratory data analysis, feature engineering, and preparation of complex, heterogeneous datasets as a basis for modeling

• Development, training, and optimization of statistical and machine learning models – such as regression and classification methods, tree-based and Bayesian methods, clustering, forecasting, or mathematical optimization – in batch and real-time contexts

• Design and execution of experiments and validations: metric definition, cross-validation, A/B tests, and checks for robustness, bias, and stability

• Design and implementation of solutions with generative AI and large language models, such as Retrieval-Augmented Generation, prompt engineering, or agentic AI approaches

• Productionizing models in collaboration with engineering teams, and coordination of data provision, data quality, and interfaces

• Design and implementation of solutions on modern cloud and data science platforms (e.g., Azure, AWS, GCP, Databricks), including associated ML and AI services

• Ensuring traceability and responsible AI use: documentation of data, models, and assumptions, reproducibility, and consideration of data protection and governance requirements

• Translation of analytical findings into management-ready decision proposals and action recommendations, advising clients on methodological issues, and moderating workshops and creating prototypes

• Co-creation of standards and best practices, conducting code and model reviews, mentoring junior and mid-level colleagues, and supporting pre-sales activities

• Completed studies in Data Science, Computer Science, Mathematics, Statistics, Physics, an MINT or Business discipline, or a comparable qualification

• >5 years of practical experience in data science or a comparable analytical role, including experience in a responsible role in project or consulting environments

• Very good programming skills in Python – including object-oriented development and common data science and ML frameworks (e.g., pandas, scikit-learn, PyTorch); knowledge of R is a plus

• In-depth methodological expertise in statistics, probability theory, and machine learning, as well as in model validation and experimental design

• Demonstrable experience in developing predictive models – such as forecasting, scoring, classification, clustering, or optimization – and in their deployment into production

• Good SQL skills and experience with relational and NoSQL databases, and understanding of ETL/ELT processes

• Practical experience with at least one cloud platform and its ML/AI services (e.g., Azure, AWS, GCP, Databricks)

• Initial practical experience with generative AI – for example, for information retrieval, analysis, or data summarization – and an understanding of its limitations

• Proficient use of version control (Git), CI/CD, and automated tests

• Strong understanding of economic contexts and the ability to recognize the business question behind an analysis

• Experience with agile working methods (Scrum/Kanban)

• Strong communication and presentation skills, confident stakeholder management, and enjoyment in sharing knowledge

• Analytical curiosity and the ability to work structurally in complex and ambiguous problem scenarios

• German language skills at C1/C2 level

• English language skills at B2 level

• Residence in Germany, ideally near Ratingen/Frankfurt

Do you know your way around these topics and feel professionally confident, even if you don't yet have more than five years of experience?

Then apply anyway! We look forward to getting to know you.

Nice to have:

• Experience in productionizing models – accompanying engineering teams or in your own responsibility – including MLOps practices such as deployment, versioning, experiment tracking, monitoring, drift detection, and retraining

• Experience in the systematic evaluation of AI solutions (e.g., quality metrics, test sets, guardrails) as well as with Responsible AI and AI Governance requirements

• Specialization in a specific area, e.g., NLP and LLMs (Transformers, Conversational AI) or Computer Vision

• Knowledge of mathematical optimization and Operations Research

• Experience with real-time and streaming inference, as well as with scalable processing frameworks like Spark

• Experience with visualization and prototyping tools (e.g., Power BI, Tableau, Streamlit) for conveying results

• Relevant cloud or ML certifications, as well as industry experience in Automotive, Retail, Banking & Insurance, or the Public Sector

• Experience with data strategy, data literacy, or business building topics, as well as in pre-sales and effort estimation

What awaits you:

• Attractive compensation & benefits – competitive salary and health budget, team offsites, modern tech equipment, mobility package, Jobrad, etc.

• Career perspective – clearly defined development opportunities & annual reviews

• Further development – continuous training, certifications, and access to industry events

• Flexibility – hybrid/remote model, flexible working hours

• Company culture – collegial, low-politics environment where your ideas and results count

Equal Opportunity:

HyPlus is an equal opportunity employer. We value diversity and are actively committed to an inclusive work environment where all employees feel welcome and valued.

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