A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.

You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.

Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.

In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.

As a Data Scientist at IBM, you will work to solve business problems using leading edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites. You will prepare, analyze, and understand data to deliver insight, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for:

• Analysis and preparation of complex data sources
• Implementing and validating predictive and prescriptive models and creating and maintaining statistical models with a focus on big data & incorporating machine learning techniques in your projects
• Writing programs to cleanse and integrate data in an efficient and reusable manner
• Development of robust machine learning pipelines
• Application of traditional machine learning algorithms as well as modern deep learning approaches (such as GenAI)
• Working in an agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviours
• Documentation and communication with internal and external clients (e.g. business departments) and stakeholders to understand and define business needs and appropriate modelling techniques to provide analytical solutions as well as presentation of proposed solutions and results.
• Evaluating modelling results and communicating the results to technical and non-technical audiences.

• Strong fundamentals in Mathematics and/or Computer Science (algorithms)
• Solid knowledge in Data science and related tools and technologies, such as Python, SQL, Pandas, NumPy, Scikit-learn, Transformers
• You're proficient at least one of the statistical programming language such as R, Python, Scala or SAS, SPSS, Matlab.
• You have a solid understanding of experience with predictive/prescriptive modeling skills
• You have strong technical and analytical abilities, a knack for driving impact and growth, and experience with programming/scripting in a language such as Java or Python.
• You're great at solving problems by looking at things differently, debugging, troubleshooting, and designing & implementing solutions to complex technical issues.
• You thrive on teamwork and have excellent verbal and written communication skills.
• Excellent verbal and written German language skills (C1 level)
• German or European Union citizenship

• You have an interest in, understanding of, or experience with Design Thinking and Agile Development Methodologies
• You have a good understanding in MLOps and related tools such as IBM Cloud Pak 4 Data, JupyterLab, Git, Docker, Helm, FastAPI, REST
• You have a good understanding of cloud and container technology (Red Hat OpenShift, AWS, Azure, etc)
• Familiarity constructing usable data sets from multiple structured and unstructured data sources
• You have preferably knowledge in the banking and financial services industry