Data Scientist: GenAI & Wave Analytics Architect

Dangote Industries Limited; Brussel Hoofdstad; Sur place; EUR 70 000 - 110 000; Plein temps

Avantages offerts par ce poste

World-class benefits

Competitive salary

Résumé du poste

McKinsey & Company in Belgium seeks a data scientist to advance Wave, our analytics SaaS for transformation programs. You will design and refine statistical models, ML methods, and GenAI-powered analytics, collaborating with cross-functional teams across EMEA.

You will work with data engineers and product managers to deliver robust analytics products on Databricks, contribute to knowledge sharing, and explain complex results to non-technical stakeholders.

Qualifications

• MSc or PhD in CS/ML/statistics/math or equivalent.
• 1+ year in data science, ML, and statistical modelling (RF, SVM, XGBoost).
• Programming in Python and SQL; basic PySpark.
• GenAI tools (Cursor, Claude) experience.
• Git and GitHub workflows; CI/CD exposure.
• Experience deploying analytics in production environments.
• Familiarity with LLMs, RAG, and prompt engineering.
• Databricks and Tableau exposure is a plus.
• Strong communication to explain analytics to non-technical stakeholders.

Responsabilités

• Collaborate with product management to build analytics products.
• Tune and evaluate LLMs using GenAI tools for segmentation tasks.
• Develop analytics methods within the Databricks platform.
• Translate analyses into actionable client insights.
• Contribute to internal knowledge sharing and documentation.
• Work within McKinsey's Wave Transformatics team in EMEA.

Connaissances

Python

SQL

PySpark

GenAI tools

Formation

MSc/PhD

Outils

Databricks

Tableau

Git

TensorFlow/PyTorch

Description du poste

McKinsey & Company in Belgium seeks a data scientist to advance Wave, our analytics SaaS for transformation programs. You will design and refine statistical models, ML methods, and GenAI-powered analytics, collaborating with cross-functional teams across EMEA.

You will work with data engineers and product managers to deliver robust analytics products on Databricks, contribute to knowledge sharing, and explain complex results to non-technical stakeholders.