AI Data Scientist
Summary
Consultant AI Data Scientist (via emagine) for a construction-industry client in Stockholm, building an Early Warnings ML solution and the Azure/Databricks ML foundation: data pipelines, models, visualization, and deployment alongside business stakeholders. Hybrid, 1-2 days/week onsite; requires Python, SQL, cloud ML experience, and Swedish.
we are looking for between 1-2 experienced AI Data Scientists for our great client within the construction industry
Start: 2026-11-18
End: 2026-05-31
Location: Stockholm, between 1-2 days/week onsite at the office
About the role:
Development of solution for business use case Early Warnings and be part of building up the foundation for ML foundation in our Azure environment. We are looking for someone who is motivated to understand the core business processes behind construction project performance — including cost, schedule, quality, and safety — and translate that understanding into practical, scalable solutions.
The team works collaboratively across business and technology to empower the organization and create measurable value.
The Data Scientist will work closely with business stakeholders to:
Translate risk hypotheses into measurable indicators
Design and develop end-to-end solutions (data pipelines, models, logic, visualization, and deployment)
Ensure insights are actionable and aligned with real project needs
Contribute to building a sustainable ML and data foundation
Your profile
As a Data Scientist in the AI Service team, you'll drive Machine Learning adoption by enhancing the analytics platform for advanced business use-cases. Build and assess proofs of concept for new applications and guide top candidates to production. Help contribute to a scalable ML platform architecture in Microsoft Azure and Databricks. Establish ML foundations at scale—cloud setup, data pipelines, and CI/CD—with the Business Analytics team. Assist with new use-cases and help stakeholders define requirements.
Must have:
English and Swedish required.
Academic degree in computer science, engineering, mathematics, or related field.
Machine learning experience with real-world applications
Data handling skills in Python and SQL
Experience with cloud platforms (preferably Azure & Databricks)
Knowledge of databases, data warehouses, or lakes
Experience in independent data exploration, validation, and visualization
Nice to haves:
Familiarity with common Large Language Model patterns
Web based frontend development
Hands-on with Databricks MLops