Research Data Scientist – Materials & AI – R&D Filler Metals

Location: Sweden Goteborg

Time Type: Full time

Job Description

Job Description:

Research Data Scientist – Materials & AI – R&D Filler Metals

Location: Gothenburg, Sweden

ESAB is a global leader in welding and cutting technologies, with over 100 years of innovation behind us. Within our Global Filler Metals organization, the R&D Filler Metals department plays a central role in shaping the future of welding materials worldwide. Our Research Team drives advanced materials research, method and tool development, and deep metallurgical expertise to support breakthrough product innovation.

We are looking for a curious and driven Data Scientist to join our Filler Metals R&D team. In this role, you will be the data and AI backbone of the research group; building the systems, models, and tools that turn raw experimental and process data into actionable scientific insight. You will work closely with R&D scientists, lab technicians, and cross-functional teams to design and deliver data-driven solutions across the full filler metal value chain. This is primarily an analytical and engineering role. While occasional lab interaction is expected to understand data sources and support measurement workflows, the core of this position is digital: modeling, automation, AI-based image analysis, visualization, and intelligent systems.

Your responsibilities:

As an R&D Filler Metals Data Scientist, you will:

• Own and develop the data architecture for Filler Metals R&D, including database design, pipelines, and integration with laboratory systems (LIMS), ensuring data is structured, traceable, and analytics-ready across the full research workflow

• Evaluate and implement modern data management tools and platforms to continuously improve data quality, accessibility, and reproducibility.

• Develop and deploy ML and statistical models to support material development, process optimization, and quality prediction.

• Lead all AI/ML-based image analysis activities within Filler Metals R&D, including microstructure quantification, defect detection, and weld quality assessment.

• Apply Design of Experiments (DoE) and advanced statistical methods to plan, analyze, and interpret research data efficiently.

• Drive the development of AI-assisted knowledge retrieval systems, including RAG pipelines and knowledge graphs, leveraging LLM platforms such as Claude, to unlock value from historical R&D reports and technical documentation.

• Act as the AI lead for Filler Metals, coordinating with company-wide AI initiatives and contributing to the broader ESAB AI community

• Provide data science support to metallurgical and materials research projects, translating experimental data into actionable insights.

• Participate in selected external research collaborations (e.g., with universities or research institutes) where data science expertise adds value.

• Occasionally support lab operations to understand measurement workflows and ensure data quality at the source.

• Communicate model outputs and analytical results clearly and concisely to both technical and non-technical audiences.

Your profile:

We believe you bring:

• M.Sc. or PhD in Data Science, Computer Science, Statistics, Metallurgy, Materials Physics, or a closely related field.

• Demonstrated experience in machine learning and statistical modeling

• Strong proficiency in Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow or similar) and SQL

• Experience with data engineering: building pipelines, managing databases, and handling structured/unstructured experimental data

• Experience with computer vision and image analysis (classical methods and/or deep learning)

• Solid understanding of statistical analysis and DoE methodology

• Familiarity with LLM applications, RAG frameworks, or knowledge graph development

• Strong skills in data visualization and dashboarding (e.g., Matplotlib, Plotly, Power BI, or similar)

• Ability to communicate complex analytical results to diverse audiences, both technical peers and business stakeholders

• Strong problem-solving skills, structured thinking, and an innovative, open-minded mindset

• Proficiency in written and spoken English

Advantageous (Merits):

• Background or working knowledge in materials science, metallurgy, or welding; understanding the physical meaning behind the data is a significant merit

• Experience in AI strategy, AI adoption, or acting as an AI champion within an organization

• Familiarity with LIMS or other laboratory information systems

• Experience working in an industrial R&D environment

• Knowledge of Swedish

What we offer:

• A dynamic and highly qualified research environment with daily interaction among scientists, engineers, welders, chemists, and technicians.
• The opportunity to work with cutting-edge technology and contribute to global, long-term research projects.
• A key role in a team shaping the future of welding metallurgy and sustainable material development.
• Professional development, scientific growth, and international collaboration with laboratories, universities, research bodies, and technology partners worldwide.

⭐ If you are passionate about metallurgy, innovation, and advancing welding technology on a global scale, we would love to hear from you.

Please apply with your CV in English.