Internship: Agentic Testing, AI-Driven Data QA

UBS

Zürich

On-site

CHF 18,000 - 25,000

Full time

6 days ago
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Job summary

UBS is offering a paid six-month global internship in Lausanne within the Compliance and Financial Crime Prevention Data Engineering team. You will design and build testing tools that mirror production data, translate business rules into safe test data, and generate robust tests.

Mentors will guide you as you gain exposure to industry practices and senior colleagues. The program emphasizes hands-on learning, collaboration, and exposure to AI-enabled testing approaches, with potential future

Qualifications

  • Completed at least 4 semesters in bachelor's program and graduation within 12 months.
  • Competitive minimum GPA of 4.5 in Swiss system.
  • Values: hard-working, trustworthy, dedicated and collaborative.
  • Strong communication and strategic thinking.
  • Experience with AI-assisted tooling and responsible use is valued.

Responsibilities

  • design and build an agentic testing assistant that understands data models and systems
  • translate transformation descriptions into reusable, privacy-safe test datasets
  • generate unit and functional tests and concise reports after validation
  • prototype GitHub Copilot integration using MCP tools and agentic components

Skills

Python programming
Data transformations
Big data frameworks (Spark/PySpark)
Software testing principles
AI ethics / responsible use

Education

Bachelor's or Master's degree in relevant field
Swiss GPA 4.5 / Swiss grading system

Job description

UBS is offering a paid six-month global internship in Lausanne within the Compliance and Financial Crime Prevention Data Engineering team. You will design and build testing tools that mirror production data, translate business rules into safe test data, and generate robust tests.

Mentors will guide you as you gain exposure to industry practices and senior colleagues. The program emphasizes hands-on learning, collaboration, and exposure to AI-enabled testing approaches, with potential future

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