Summer 2026 Manufacturing Business Process Intern

Job Description

Skydio is seeking a Summer 2026 Manufacturing Business Process Intern to enhance efficiency and scalability within its production and RMA (Return Merchandise Authorization) processes. This role offers a unique opportunity to work at the forefront of autonomous flight technology, collaborating with a multidisciplinary team dedicated to empowering a diverse range of drone users.

About Skydio

Skydio stands as the leading US drone company and a global pioneer in autonomous flight, which is recognized as the pivotal technology for the future of drones and aerial mobility. The company’s strength lies in its team’s profound expertise in artificial intelligence, exceptional hardware and software product development, operational excellence, and an unwavering commitment to customer satisfaction. Skydio aims to serve a broad and diverse audience, from utility inspectors and first responders to soldiers in critical battlefield scenarios and beyond.

About The Role: Summer 2026 Manufacturing Business Process Intern

As a Summer 2026 Manufacturing Business Process Intern, you will be instrumental in driving efficiency and scalability across Skydio’s production and RMA processes. This highly cross-functional and hands-on internship involves close collaboration with key departments including Production, Quality, Supply Chain, Finance, and Customer Support. Your responsibilities will include analyzing current workflows, designing measurable improvements, and implementing practical solutions to reduce costs, improve cycle times, and enhance the accuracy of reports and invoices. You will actively engage on the factory floor, within systems, and directly with stakeholders to deliver tangible, production-ready outcomes.

How You’ll Make An Impact

Your contributions will focus on several key initiatives, each with specific deliverables:

• Analyze & Redesign the X10 Drone Estimate Process

  Goal: To ensure accurate cost coverage and provide customers with reliable, auditable estimates, reports, and invoices.

  Deliverables:

  • A comprehensive documented current-state process and a detailed gap analysis, identifying stakeholders, systems, data sources, and pain points.
  • A redesigned end-to-end cost model and workflow that accurately captures direct and indirect costs, RMA labor/materials, test and repair steps, and margin rules.
  • An implementation plan for automating estimate calculations (utilizing spreadsheets + scripts / ERP configuration), outlining integration points with invoicing/Finance systems, and establishing reconciliation controls.
  • End-to-end test cases, sample reports/invoices, training materials, and a rollout plan complete with risk assessment and rollback steps.
• Build Near Real-Time Production Dashboards for Operators and Supervisors

  Goal: To provide operators and supervisors with immediate visibility into critical Key Performance Indicators (KPIs) to facilitate faster decision-making and improved throughput.

  Deliverables:

  • High-level and station-level dashboards (using tools like Looker, Tableau, Power BI, or embedded web dashboards) displaying essential KPIs: Overall Equipment Effectiveness (OEE), yield, cycle time, Work-In-Progress (WIP), and rejects.
  • Drill-down capabilities to failed units and unit-level traceability to identify defect clusters and their root causes.
  • Operator-facing views and low-latency displays specifically designed for the shop floor environment.
  • Mockups, data models, implementation notes (including data sources, latency, and ETL/streaming approach), a validation plan, and a phased rollout plan (from pilot to full production).
• Implement Inventory Control and Reorder-Point Triggers for Production Lines

  Goal: To minimize stockouts and excess inventory while ensuring that production lines consistently have the necessary parts available.

  Deliverables:

  • A robust reorder point and safety stock methodology specifically tailored to each production line, considering demand variability, lead times, and service-level targets.
  • Configurable reorder triggers and a workflow for initiating purchases or pull requests (including ERP/MRP configuration notes).
  • An implementation plan for continuous monitoring and automated alerts, complemented by dashboards showing inventory health and reorder status.
  • Pilot execution and validation, encompassing test scenarios, defined success metrics, and a comprehensive rollout checklist.
• Improve RMA & Disposition Workflows (Additional Focus)

  Goal: To reduce RMA cycle time, enhance disposition accuracy, and maximize cost recovery where feasible.

  Deliverables:

  • A clear RMA process map detailing proposed improvements, including triage rules, disposition codes, and opportunities for automation.
  • Dashboards and reports for tracking critical RMA KPIs such as turnaround time, disposition mix, and cost recovery.
  • An implementation and training plan for all process and system changes.

What Makes You a Good Fit

The ideal candidate will excel by demonstrating a blend of process-oriented thinking, data analysis skills, and practical understanding of manufacturing operations:

• Currently pursuing a degree in Industrial Engineering, Manufacturing Engineering, Operations Research, Computer Science, Data Science, or a related technical field.
• Familiarity with Business Intelligence (BI) tools such as Looker, Tableau, or Power BI, along with practical experience in building dashboards or mockups.
• Strong proficiency in Excel modeling and proven experience in developing cost models or process simulations.
• A solid understanding of manufacturing metrics and shop-floor concepts (e.g., OEE, takt time, cycle time, yield, WIP) and fundamental inventory concepts (e.g., safety stock, reorder points).
• Comfortable working directly on the factory floor to gather requirements and validate proposed solutions.
• Exceptional communication skills, enabling effective collaboration with Production, Quality, Supply Chain, Finance, and Customer Support to define requirements and present results.
• A proactive problem-solver, capable of tackling ambiguous process challenges and delivering reproducible analyses, models, and implementation plans.
• Detail-oriented with a strong documentation mindset, proficient in creating process maps, data contracts, and test cases.

Compensation

The hourly base salary range for this position is: $41/hr for Undergraduate students, $47/hr for Graduate students, and $53/hr for PhD students*. Compensation will be determined based on various factors including skill level, proficiencies, transferable knowledge, and experience. In addition to the base salary, Skydio full-time employees are eligible for enrollment in our benefit plans and can take advantage of a variety of incentives and stipends.

For some positions, the pay may vary depending on the individual’s regional location.

At Skydio, we firmly believe that diversity fuels innovation. We have cultivated a multidisciplinary environment that embraces the power of diverse perspectives to engineer elegant solutions for complex challenges. We are dedicated to expanding our network of people, programs, and resources to foster a truly inclusive culture.

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or other characteristics protected by federal, state, or local anti-discrimination laws.

For positions located in the United States of America, Skydio, Inc. utilizes E-Verify to confirm employment eligibility. To learn more about E-Verify, including your rights and responsibilities, please visit https://www.e-verify.gov/.