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.

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.

• Good interpersonal, communication and customer relationship skills
• Experience of applying advanced analytics and predictive modelling techniques in a professional context
• Experience of working within an Agile environment
• Experience with SQL and NoSQL databases
• Experience with Azure, AWS, GCP or IBM cloud platforms is a plus
• Experience with models from Hugging Face, FastAPI, Transormers, Pydantic, OpenCV

Your Role and Responsibilities
As Data Scientist at IBM, you will work to solve business problems using Python (from scripts to applications), 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.

Your primary responsibilities include:
• Designing and developing challenging solutions that automate various aspects of data acquisition, ingestion, storage, access and transformation of data.
• You will leverage a variety of machine learning techniques to solve data related challenges.

We value curiosity, teamwork, and a desire to learn. We are confident that if you possess the right attitude, work ethic, and skillset that you could succeed in the role.

Required Technical and Professional Expertise
• Education in a quantitative field (e.g., Computer Science, Economics, Engineering, Mathematics, Finance, Statistics, Operations Research, Physics)
• Coursework in mathematics, statistics, machine learning, and data mining, feature engineering
• High level of comfort with various data types and structures: structured versus unstructured data
• Experience in data cleaning, validation, integration
• Strong understanding of multivariate statistical and machine learning algorithms, such as principal component analysis, neural networks, discriminant analysis, linear and logistic regression, k-nearest neighbors, classification and regression tree, etc.
• Well versed/ good understanding of Python programming language
Toolbox: Pandas, Scikit-learn, Numpy, Matplotlib, Github, TensorFlow, Flask

Preferred Technical and Professional Expertise
Expertise:
• Basic understanding of Large Language models.
• Experience of applying advanced analytics and predictive modelling techniques in a professional context
• Experience of working within an Agile environment
• Experience with SQL and NoSQL databases
• Experience with Azure, AWS, GCP or IBM cloud platforms is a plus
• Experience with models from Hugging Face, FastAPI, Transormers, Pydantic, OpenCV

Benefits:
• Private health insurance, life insurance, critical illness insurance
• To be part of international projects based on your experience, career goals and personal aspirations
• Dynamic work in projects for customers from Fortune 500 companies list
• Premium, full life-cycle work experience on high-profile IT solutions with direct impact on people and businesses
• Personalized professional growth, mentoring, training and clear career progression
• Flexible work & life balance
• Hybrid work model
• Competitive salary and additional bonuses.
• Monthly salary for this position is from 2000 EUR gross to 5300 EUR gross.
* The final offer will be dependent on qualifications, professional experience and competencies.