AI Data Scientist (all genders)

Job-ID: 15956; Location(s): Krakow 

We are seeking a highly skilled and motivated hands-on AI Data Scientist (all genders) with a strong foundation in both traditional machine learning techniques and cutting-edge generative AI methodologies. This role is pivotal in designing, developing, and deploying impactful data-driven solutions to solve complex challenges within our manufacturing operations. The ideal candidate possesses deep expertise in Python, a proven ability to translate business problems into data science solutions, and significant experience or understanding of manufacturing processes, data, and objectives (e.g., yield improvement, quality control, predictive maintenance, process optimization, supply chain efficiency).

This position is exclusively located at our IT Site in Krakow, Poland. 

Key Responsibilities:

1. Model Development & Implementation (Traditional AI):
• Design, build, train, and deploy supervised and unsupervised machine learning models using Python to address manufacturing challenges such as predictive maintenance, anomaly detection, root cause analysis, quality prediction/control, yield optimization, and demand forecasting
• Utilize statistical modeling and machine learning techniques on diverse manufacturing datasets (e.g., sensor data, MES, ERP, quality logs, supply chain data)
• Perform rigorous feature engineering, model selection, validation, and performance monitoring
2. Generative AI Exploration & Application:
• Explore, evaluate, and implement generative AI models (including LLMs, and potentially diffusion models or others) for relevant use cases
• Employ techniques like prompt engineering, fine-tuning, and Retrieval-Augmented Generation (RAG) to optimize generative AI solutions
3. Data Analysis & Pipeline Development:
• Conduct in-depth exploratory data analysis (EDA) to uncover insights and identify opportunities
• Clean, preprocess, and transform large, complex datasets using Python libraries (Pandas, NumPy, etc.)
• Collaborate with data engineers to build and maintain robust data pipelines for model training and deployment
4. Business Acumen & Collaboration:
• Partner closely with manufacturing engineers, process experts, plant managers, supply chain analysts, and other business stakeholders to understand operational challenges and define project requirements
• Translate complex business needs into well-defined data science problems and solutions
• Effectively communicate findings, methodologies, and results to both technical and non-technical audiences through visualizations, reports, and presentations
5. Technology & Best Practices:
• Stay current with the latest advancements in data science, machine learning, generative AI, and MLOps practices
• Champion the use of Python as the primary language for data science development within the team
• Contribute to establishing best practices for model development, validation, deployment, and monitoring (MLOps)
  
  

Required Qualifications:

• Master's or PhD in Computer Science, Statistics, Engineering, Physics, Mathematics, or a related quantitative field (or Bachelor's degree with significant equivalent experience)
• Proven hands-on experience (typically 3-5+ years) as a Data Scientist, developing and deploying machine learning models in real-world/production environments
• Strong proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn)
• Solid understanding and practical experience with a range of traditional machine learning algorithms (e.g., regression, classification, clustering, time series analysis, dimensionality reduction)
• Demonstrated experience or strong theoretical understanding of Generative AI concepts and techniques, particularly Large Language Models (LLMs), prompt engineering, and fine-tuning approaches Familiarity with frameworks like Hugging Face Transformers, LangChain, etc.
• Experience querying and manipulating data using SQL
• Proven ability to understand complex business processes, particularly within a manufacturing context (e.g., understanding of concepts like OEE, SPC, BOMs, process flow, quality metrics)
• Excellent problem-solving skills and analytical thinking
• Strong communication and collaboration skills

Preferred Qualifications:

• Direct work experience within a manufacturing company or consulting for manufacturing clients
• Experience applying AI/ML specifically to manufacturing problems (e.g., predictive maintenance, visual inspection, process optimization)
• Experience with deep learning frameworks (TensorFlow, PyTorch)
• Experience with cloud platforms (AWS, Azure, or GCP) and their respective ML services (e.g., SageMaker, Azure ML, Vertex AI)
• Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, CI/CD for ML)
• Experience working with Big Data technologies (e.g., Spark, Hadoop)
• Familiarity with vector databases (e.g., Pinecone, Chroma, Weaviate)
• Knowledge of manufacturing execution systems (MES), ERP systems, and industrial IoT (IIoT) data
• Understanding of process improvement methodologies (e.g., Lean, Six Sigma)

What We Offer

• A dynamic working environment with exciting projects in the field of artificial intelligence and machine learning
• The opportunity to utilize innovative technologies and actively contribute to their further development
• A motivated team looks forward to working with you. Our strong team spirit helps us achieve our common goals
• Stability and career growth: As a growing family-owned company with an international focus, Viega offers both
• Comprehensive onboarding and training through our Viega Academy to support you in your role and personal development

Your contact person:

Anne Ferchau  -  Anne.Ferchau@viega.de - +49 (2722) 61 - 5893