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Manufacturing Business Process Intern

Job in Hayward, Alameda County, California, 94557, USA
Listing for: Skydio
Apprenticeship/Internship position
Listed on 2026-03-12
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst
Salary/Wage Range or Industry Benchmark: 41 - 53 USD Hourly USD 41.00 53.00 HOUR
Job Description & How to Apply Below

Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best‑in‑class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders, soldiers in battlefield scenarios and beyond.

About

the Role

As a Summer 2026 Manufacturing Business Process Intern, you will help drive efficiency and scale in Skydio’s production and RMA processes. You’ll partner closely with Production, Quality, Supply Chain, Finance, and Customer Support to analyze current workflows, design measurable improvements, and implement practical solutions that reduce cost, improve cycle time, and increase accuracy of reports and invoices. This internship is highly cross‑functional and hands‑on — you will spend time on the factory floor, in systems, and with stakeholders to deliver production‑ready outcomes.

How

You’ll Make an Impact

1) Analyze & redesign the X10 Drone Estimate Process

Goal:
Ensure we are covering costs and providing customers with accurate, auditable estimates, reports, and invoices.

Deliverables:

  • A documented current‑state process and gap analysis (stakeholders, systems, data sources, pain points).

  • A redesigned end‑to‑end cost model and workflow that captures direct and indirect costs, RMA labor/materials, test and repair steps, and margin rules.

  • Implementation plan to automate estimate calculations (spreadsheet + script / ERP configuration), integration points with invoicing/Finance systems, and reconciliation controls.

  • End‑to‑end test cases, sample reports/invoices, training materials, and a rollout plan with risk/rollback steps.

2) Build near real‑time production dashboards for operators and supervisors

Goal:
Provide operator‑ and supervisor‑facing visibility into critical KPIs to enable faster decision making and improved throughput.

Deliverables:

  • High‑level and station‑level dashboards (Looker/Tableau/Power BI or embedded web dashboards) showing KPIs: OEE, yield, cycle time, WIP, rejects.

  • Drill‑downs to failed units and unit‑level traceability to identify defect clusters and root causes.

  • Operator‑facing views / low‑latency displays designed for the shop floor.

  • Mockups, data model, implementation notes (data sources, latency, ETL/streaming approach), validation plan, and a phased rollout plan (pilot → full production).

3) Implement inventory control and reorder‑point triggers for production lines

Goal:
Reduce stockouts and excess inventory while ensuring production lines have the parts they need when they need them.

Deliverables:

  • Reorder point and safety stock methodology tailored to each production line (including demand variability, lead times, and service‑level targets).

  • Configurable reorder triggers and workflow for triggering purchases or pull requests (ERP/MRP configuration notes).

  • Implementation plan for monitoring and automated alerts, plus dashboards that show inventory health and reorder status.

  • Pilot execution and validation (test scenarios, success metrics, and rollout checklist).

4) Improve RMA & disposition workflows (additional focus)

Goal:
Shorten RMA cycle time, improve disposition accuracy, and recover costs where possible.

Deliverables:

  • RMA process map and proposed improvements (triage rules, disposition codes, automation opportunities).

  • Dashboards and reports tracking RMA KPIs (turnaround time, disposition mix, cost recovery).

  • Implementation and training plan for process and system changes.

What Makes You a Good Fit

You’ll thrive if you have a mix of process thinking, data skills, and a 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 BI tools (Looker, Tableau, Power BI) and experience building dashboards or mockups.

  • Strong Excel modeling skills and experience building cost models or process simulations.

  • Understanding of manufacturing metrics and…

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