Graduate AI & Data Engineer — Global Tech Office

UBS; Zürich; Vor Ort; CHF 70.000 - 110.000; Vollzeit

Zusammenfassung

UBS is seeking ambitious graduates to join the 2027 Group Technology Office Graduate Talent Program in Zurich. You design and build AI-ready data mesh capabilities for Global Investment Management Discretionary Mandates and develop data products that support reporting, analytics, ML and generative AI solutions.

You will work with engineers, data owners and business stakeholders to define data domains, ownership models, metadata standards, quality controls and data lineage while exploring

Qualifikationen

• recent graduate (graduated in the last 24 months)
• no more than two years of full-time work experience
• Bachelor's or Master's in a MINT field
• GPA of at least 4.5 on the Swiss scale
• knowledge of software engineering, data engineering, cloud technologies and modern data architectures
• experience with AI, machine learning or generative AI and responsible AI

Aufgaben

• design and build an AI-ready Data Mesh for Global Investment Management Discretionary Mandates
• develop data products for reporting, analytics, ML and generative AI
• collaborate with engineers, data owners and stakeholders to define data domains, ownership models, metadata standards, quality controls and lineage
• bring innovative ideas to innovate

Kenntnisse

Data engineering

Software engineering

Cloud technologies

Modern data architectures

AI / ML curiosity

Communication skills

Strategic thinking

Collaboration

Hard-working

Ausbildung

Bachelor's or Master's in a MINT field

Jobbeschreibung

UBS is seeking ambitious graduates to join the 2027 Group Technology Office Graduate Talent Program in Zurich. You design and build AI-ready data mesh capabilities for Global Investment Management Discretionary Mandates and develop data products that support reporting, analytics, ML and generative AI solutions.

You will work with engineers, data owners and business stakeholders to define data domains, ownership models, metadata standards, quality controls and data lineage while exploring