Data Science Consultant: GenAI and ML for Global Projects

Sia; Rotterdam; On-site; EUR 60,000 - 85,000; Full time

Benefits offered by this job

Health insurance

Pension plan

International projects

Job summary

Sia is seeking a Data Science Consultant to join the Amsterdam Data Science team. You will work with multidisciplinary groups to apply advanced analytics, ML, and GenAI to real client challenges and deliver impactful, data-driven results.

You will collaborate with Data Scientists, Data Engineers and Consultants, develop statistical models and optimization approaches, and present findings while contributing to knowledge sharing within a supportive, international environment.

Qualifications

• Master’s degree in Data Science, Econometrics, Applied Mathematics, Computer Science, (Energy) Engineering or related technical field with substantial programming.
• 1–3 years of relevant professional experience.
• Strong coding in Python and at least one additional analytical language (e.g., R, SQL).
• Solid knowledge of Machine Learning techniques, optimization methods, and Generative AI.
• Exposure to cloud platforms (AWS, Azure, GCP) is a plus.
• Fluent in English and Dutch, both written and oral.

Responsibilities

• Collaborate with Data Scientists, Data Engineers and Consultants on client projects in multidisciplinary teams.
• Develop and apply statistical models, optimization solutions and advanced ML techniques.
• Apply Generative AI and large language models to create innovative solutions for clients.
• Present analytical results clearly and facilitate client workshops.

Skills

Python

R/SQL

Machine learning

Education

WO Master’s in Data Science or related

Tools

AWS

Azure

GCP

Job description

Sia is seeking a Data Science Consultant to join the Amsterdam Data Science team. You will work with multidisciplinary groups to apply advanced analytics, ML, and GenAI to real client challenges and deliver impactful, data-driven results.

You will collaborate with Data Scientists, Data Engineers and Consultants, develop statistical models and optimization approaches, and present findings while contributing to knowledge sharing within a supportive, international environment.