Working Student - Distributor Product Data Improvement (m/f/d)

Job title: Working Student - Distributor Product Data Improvement (m/f/d)

About the Role Corning's Optical Communications segment is seeking a Working Student – Distributor Product Data Improvement (m/f/d) at our Berlin headquarters. You will support data quality improvements across multiple systems to enable reliable distributor datasets, contributing to data-driven decisions and faster go-to-market.

What You'll Do

• Support the improvement of product data quality across multiple systems by analyzing data sets, identifying gaps, and contributing to structured data updates for key products.
• Collaborate with cross-functional teams to ensure product information is correct, complete, and consistent, enabling reliable datasets for distribution channels.
• Help build transparency and simple data tools (e.g., dashboards) while supporting ongoing data analytics and process-improvement initiatives.
• Leverage AI capabilities to increase effectiveness of current processes.

What We're Looking For

• Currently enrolled at a university, preferably in Business Administration, Data Analytics, or a similar degree program.
• Strong analytical mindset and great attention to detail.
• Structured and proactive work style, with the ability to manage multiple tasks.
• Strong Excel skills and interest in data and dashboards.
• Interest in data analytics, digital tools, and process improvement.
• Fluent in both German and English (written and spoken), comfortable working across teams.
• Available to work 20 hours per week during the semester and up to 40 hours per week during semester breaks.

Nice to Have

• Hands-on experience with data analytics tools such as Power BI, Databricks, or Copilot-based Agents.

Compensation & Benefits

• Attractive hourly wage and flexible working hours.
• Dynamic and international working environment in Berlin.
• Opportunity to take ownership of independent workstreams after onboarding.
• Opportunity for long-term development and potential full-time career path.
• Exposure to cross-functional collaboration across product, operations, and commercial teams.
• Hands-on experience in data analytics tools.