AI-Powered Process Improvement Intern (Logistics)

Amazon; Tees Valley; On-site; GBP 12,000 - 20,000; Full time

Job summary

Amazon UK Services Ltd. is offering an internship as a Process Improvement Specialist at the MME1 Fulfillment Center in Darlington. You will work in a warehouse environment, focusing on improving driver experience, efficiency, and safety using AI tools and data analytics.

You will plan continuous improvement initiatives, analyse feedback, and collaborate with station management to implement data-driven solutions across the site, with potential to share best practices within the EU network.

Qualifications

• Currently in penultimate or final year and pursuing a degree in business, supply chain, transportation, economics or similar.
• Analytical with advanced Excel skills (formulas, pivot tables, macros).
• Fluent English (C1) in speaking, writing and reading.
• Ability to work 40 hours/week minimum and commit to 3–12 month internship.
• Experience communicating with a wide range of stakeholders.

Responsibilities

• Plan and implement continuous improvement initiatives to innovate driver experience.
• Use AI tools and data analytics to identify inefficiencies and prototype solutions.
• Analyse feedback and use data to own site-wide process improvements.
• Collaborate with station management and stakeholders to solve process issues.
• Audit processes for compliance and support decisions with analytics.

Skills

English fluency (C1)

Data analytics

Advanced Excel

Stakeholder communication

Analytical thinking

Python or SQL knowledge

Education

Penultimate or final year degree in business/supply chain/economics

Tools

Minitab

JMP

MS Excel

MS Access

Job description

Amazon UK Services Ltd. is offering an internship as a Process Improvement Specialist at the MME1 Fulfillment Center in Darlington. You will work in a warehouse environment, focusing on improving driver experience, efficiency, and safety using AI tools and data analytics.

You will plan continuous improvement initiatives, analyse feedback, and collaborate with station management to implement data-driven solutions across the site, with potential to share best practices within the EU network.