As the world and the way people live is changing, we at Bekaert believe it’s our responsibility to contribute to finding new solutions for the future. With a 140+ year old heritage of excellence, innovation, and a future‑focused mindset, we strive to create value for our customers and society. We aim to do this through innovative solutions and sustainable practices. We are committed to pushing the boundaries of steel wire transformation and coatings whilst also leveraging our expertise to develop innovative solutions with new materials and services in a safe, smart, and sustainable way. Our focus extends to markets such as new mobility, low‑carbon construction, and green energy.
Make sure to read the full description below, and please apply immediately if you are confident you meet all the requirements.
As a dynamic and growing company with over 19,000 employees worldwide, 75 nationalities, a retention rate above 90% and €3.7 billion in combined revenue in 2025, we are looking for someone like you to join our team as we continue to shape a safer, more efficient, and connected world!
Purpose and Mission
Bekaert is leading transformation program to enhance end‑to‑end user experience and deliver user journeys that drive impact across multiple cross‑functional processes. Bekaert’s employees, suppliers and customers across the value chain are getting increasingly sophisticated and expect a seamless and well‑designed user experience. Bekaert organization is reviewing the success and performance of these end‑to‑end user journey through data analytics, reporting and governance across the journey.
To strengthen our data science and analytics capabilities, you will join us in the role of “Data Scientist” in Data and Analytics Platform team. You are accountable to model complex business problems and discover business insights through the use of statistical, algorithmic, mining, and visualization techniques. You will collaborate with cross‑functional stakeholders to understand the business usage of data, architect specialized database and computing environments and communicate recommendations to enable decision‑making.
Key Activities and Responsibilities
Problem Analysis and Project Management
Guide and inspire the organization about the business potential and strategy of artificial intelligence
Identify data‑driven / ML business opportunities
Collaborate across business teams to understand IT and business constraints
Prioritize, scope, and manage data science projects and corresponding key performance indicators (KPIs) for success
Define and communicate governance principles
Data Collection and Integration
Understand new data sources and process pipelines and catalog/document them
Acquire access to various databases and other source systems such as SQL or graph databases
Create data pipelines for more efficient and repeatable data science projects
Data Exploration and Preparation
Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering, principal components analysis (PCA)
Generate hypotheses about the underlying mechanics of the business process
Test hypotheses using various quantitative methods
Display drive and curiosity to understand the business process to its core
Network with domain experts to better understand the business mechanics that generated the data
Machine Learning
Apply ML and advanced analytics techniques to perform classification or prediction tasks
Integrate domain knowledge into the ML solution, for example, from an understanding of financial risk, customer journey, quality prediction
Validation & optimization of models
Generative & Agentic AI
Use generative AI to extract insights out of unstructured datasets
Use agentic concepts to improve quality of the results
Operationalization
Collaborate with ML Ops Engineer to evaluate and implement ML deployment options
Integrate model performance management tools into the current business infrastructure
Implement champion/challenger test (A/B tests) on production systems
Continuously monitor execution and health of production ML models
Establish best practices around ML production infrastructure
Other
Train other business and IT staff on basic data science principles and techniques
Promote collaboration with other data science teams within and external to organization
Work within an agile delivery methodology in a leading role
Skills
Competencies
Organizationally savvy, with the ability to navigate organizational politics
Ability to articulate new ideas and concepts to technical and non‑technical audiences
Ability to understand the long‑term ("big picture") and short‑term perspectives of situations
Ability to translate future‑state business capabilities and requirements into solution requirements
Ability to propose and estimate the financial impact of solution alternatives
Ability to assess product quality and other non‑functional attributes and provide recommendations
Characteristics
You are a leader and an entrepreneur that people willingly follow
Displays intellectual curiosity and integrity
Motivated and driven by achieving long‑term business outcomes
High level motivational skills so that you can also manage virtual teams
Good written and verbal communication skills
Ability to work within an IT organization in an in‑and‑out outsourced environment
Previous Experience
You will ideally have a specialization in ML, AI, cognitive science or data science
At least 3 years of progressive relevant experience in data science; successfully launching, planning, and executing significant data science projects. Experience building and deploying predictive models, web scrapping, and scalable data pipelines
Experience with statistical software, scripting languages, and packages. Python/Jupyter is required. Others (e.g. MATLAB) are appreciated
Experience with the data science platforms - Azure Machine Learning. Others (e.g. Google Cloud ML) are appreciated
Knowledge and experience in statistical and data mining techniques - generalized linear model /regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, neural network, graph analysis, etc
Experience on Open‑source data science libraries (e.g. sklearn, Tensorflow,...), open‑source visualisation libraries (e.g.Plotly Dash/Bokeh, Streamlit, ..)
Experience with popular database programming languages including SQL
Experience of Data Visualisation Products such as Power BI is a plus
Experience with large language models and prompt engineering
Good understanding of agile principles and development methodologies and capability of supporting agile teams by providing advice and guidance on opportunities, impact and risks
Good analytical, planning and organizational skills. Be a voice of reason to make tough calls
Qualifications and Education
Master degree or PhD in computer science, data science, operations research, statistics, applied mathematics is required
Be bold and take the leap!
We're looking for individuals who are not afraid to take risks and explore new ideas. If you are passionate about personal growth and bringing your authentic self to work, we want you on our team!
At Bekaert, we celebrate diversity and are committed to creating an inclusive work environment. xlxgzvr We do not discriminate based on race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.
To learn more about us and our exciting career opportunities, visit Bekaert Careers
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