AI Data Scientist (all genders)
AI Data Scientist (all genders)
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
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:
- 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
- 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
- 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
- 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
- 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:
- Masters or PhD in Computer Science Statistics Engineering Physics Mathematics or a related quantitative field (or Bachelors 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 49 (2722) 61 - 5893
Employment Type
Full Time
