Introduction



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



You will 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 will 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 will 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.







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.





Your role and responsibilities



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 insights, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for:


- Analysis, preparation and management 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 scalable and robust data and machine learning pipelines
- Application of traditional machine learning algorithms as well as modern deep learning approaches (such as GenAI)
- Implementation, integration and monitoring of AI / ML models
- 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 and IT 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.




Required education

Bachelor's Degree



Preferred education

Master's Degree



Required technical and professional expertise


- Strong fundamentals in Mathematics and/or Computer Science (algorithms)
- Proven knowledge and experience in
- Foundational knowledge of Celonis
- SQL / Data Modelling for Process Mining experience
- PQL / Analysis Building for Process Mining experience

- Strong ability to communicate with and coach senior executives, translating technical insights into business strategy
- You have strong technical and analytical abilities, a knack for driving impact and growth, and experience with programming/scripting in 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)




Preferred technical and professional experience


- Azure platform expertise, ideally with Azure Foundry and related AI/ML services
- Experience in DevOps and MLOps, including CI/CD pipelines, ML lifecycle management, and deployment
- Foundational knowledge in the chemical or process industry, with awareness of domain-specific challenges and data
- Experience in consulting or client-facing roles with a focus on value realization through AI
- First experience with Object Centric Process Mining
- Foundational knowledge of advanced Celonis functionalities (AI Features, Annotation Builder, Action Flows, Orchestration Engine)






Schlagworte: Hybrid, Data Analytics, Entry Level, Englisch, Softwareentwicklung, Python, Softwareentwickler, Designer, designer, Webentwickler, AI, Anwendungsentwicklung, Anwendungsentwickler, Salesforce, KI, Grafiker, Azure, webdesigner, Webdesigner, Programmierer, Empfehlungsbund
Quelle/Bewerbung via: [https://www.empfehlungsbund.de/jobs/291216/data-scientist-process-mining-m-strich-w-strich-d](https://www.empfehlungsbund.de/jobs/291216/data-scientist-process-mining-m-strich-w-strich-d#apply_form)

#### Kurzinfo zum Unternehmen

Die IBM Client Innovation Center Germany GmbH (CIC) ist eine hundertprozentige IBM-Tochtergesellschaft. Bei uns herrscht die pulsierende Aufbruchstimmung einer unternehmerischen Neugründung verknüpft mit der Souveränität eines erfahrenen und erfolgreichen Traditionsunternehmens. Eingebettet in das globale IBM-Netzwerk bieten unsere motivierten und stetig wachsenden Teams hochwertige IT-Services Made in Germany und können dabei auf das Technologiewissen und die Branchenexpertise von IBM zurückgreifen. Neben unserem Hauptstandort Magdeburg hat das CIC Niederlassungen in Frankfurt, Köln und München.