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Website IBM

IBM Associate Data Scientist – Client Innovation Center (Germany)

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Opportunity Overview

Attribute Details
Organization IBM Consulting (IBM Client Innovation Center Germany GmbH)
Role Title Associate Data Scientist (f/m/x)
Job Locations Frankfurt (Hesse), Cologne (North Rhine-Westphalia), Munich (Bavaria), Magdeburg (Saxony-Anhalt), Germany
Work Arrangement Hybrid (Up to 40% travel / 2 days a week based on client needs)
Domain Focus GenAI Architectures, RAG Systems, Agentic AI, MLOps, Enterprise Data Science
Experience Level Entry Level / Early Career
Language Requirement Mandatory C1 German Fluency (Verbal & Written) + Professional English
Application Fee Free

Role Scope & Technical Architecture

The Associate Data Scientist within the Hybrid Cloud & Data service line solves complex enterprise client problems using open-source tools, IBM AI application suites, and modern Agentic AI workflows:

[Complex Enterprise Data Sources] ➔ [Data Cleansing & MLOps Pipelines] ➔ [GenAI / RAG / Agentic Models] ➔ [Scalable Cloud / OpenShift Deployment]

Core Responsibilities

  • GenAI & Agentic Development: Implement predictive, prescriptive, and generative AI solutions using Retrieval-Augmented Generation (RAG), agentic patterns, and deep learning frameworks.

  • Data Engineering & Pipelines: Write clean, reusable Python/R programs to cleanse, integrate, and manage complex big data sources for production ML models.

  • MLOps & Model Lifecycle: Build, validate, deploy, and monitor scalable ML models using CI/CD pipelines, MLOps practices, and containerised environments.

  • Consulting & Stakeholder Management: Collaborate with cross-functional IT and business stakeholders in German and English, translating complex statistical outputs into actionable client recommendations.

Candidate Eligibility & Technical Skills Matrix

Minimum Qualifications

  • Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, or a related quantitative field (Master’s degree preferred).

  • Language Proficiency: C1 Level fluency in German (written and verbal) is required for client-facing consulting across DACH markets.

  • Technical Fundamentals: Strong foundational knowledge in algorithms, mathematics, and Python/R programming.

  • GenAI & MLOps Core: Practical exposure to GenAI, RAG, agentic AI frameworks, PyTorch/TensorFlow, and MLOps lifecycle execution.

Technical & Cloud Skill Matrix

Category Skill Domain & Focus Areas
AI Frameworks & Patterns

• Frameworks: PyTorch, TensorFlow, Scikit-Learn


• Architectures: RAG, Agentic AI patterns, LLM fine-tuning, Transformers
MLOps & Software Engineering

• CI/CD automation, model packaging, containerization, model monitoring


• Data integration, reusable ETL pipelines, Git version control
Cloud & Infrastructure (Preferred)

• Red Hat OpenShift, AWS, Azure, or IBM Cloud platform experience


• Familiarity with AI Governance, model drift, and ethical AI auditing
Consulting Competencies

• Analytical problem-solving, debugging, and agile collaboration


• Executive communication and client-centric consulting mindset

Selection Workflow & Evaluation Stages

[Application & Profile Screening] ➔ [Recruiter Phone Screen] ➔ [Technical AI/GenAI Assessment] ➔ [Consulting & Behavioral Loop]

  1. Profile Screening: Verification of computer science/math educational credentials, C1 German language proficiency, and location preference (Frankfurt, Cologne, Munich, Magdeburg).

  2. Recruiter Discussion: Review of candidate background, consulting mobility (up to 40% travel), and alignment with IBM Client Innovation Center projects.

  3. Technical Interview Loop: Deep dive into data structure fundamentals, Python coding, MLOps architectures, RAG design, and hands-on ML modelling scenarios.

  4. Consulting & Partner Loop: Case study presentation evaluating problem-solving under ambiguity, stakeholder management skills, and German-language business communication.

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