Overview

The Product team sets the roadmap for a robot fleet deployed across more than 40 countries, but the raw material for those decisions — cloud telemetry, field incident reports and operator feedback — sits in separate systems and is analysed case by case. This internship builds a repeatable loop that turns that data into product decisions: quantify how robots are actually used, research the people using them, prototype the fix, and write the requirements the engineering team builds from. The intern works across product management, UX and data analysis rather than specialising in one.

Key Responsibilities

• Data — Extract, clean and analyse fleet telemetry from LionsCloud (task completion, cleaning coverage, interruption and error events) and build a recurring dashboard that reports fleet health by product line and region.

• Data — Consolidate field incident and voice-of-customer records into one tracker and produce monthly fleet-normalised prevalence analysis, so issues are ranked by real-world impact rather than by whoever escalated loudest.

• UX — Run structured user research with cleaning operators, service technicians and distributors, including on-site observation at customer deployments, and turn the findings into journey maps and a prioritised list of friction points.

• UX — Wireframe and prototype improvements to the on-robot interface and the LionsCloud web and mobile app in Figma, then run lightweight usability tests with five to eight operators per iteration.

• Product — Write requirement briefs and user stories for the top-ranked improvements, including acceptance criteria, and support the Product Manager through release planning and release-note review.

• Product — Own one small feature end to end under supervision: problem definition, data evidence, design, specification, validation, and post-release measurement.

Deliverables

• A live fleet-performance dashboard with documented metric definitions and data caveats, handed over to the Product team in working condition.

• A field research report covering at least ten operator or technician interviews and three site visits, with journey maps and a ranked friction list.

• A clickable Figma prototype for the highest-priority improvement, with usability test results and recommended changes.

• One approved requirement document for a shipped or roadmapped feature, written to the team’s existing format, with acceptance criteria and explicit out-of-scope items.

• A repeatable playbook for the insight loop (queries, research script, templates) that the next person can run without the intern present.

• Final presentation to Product, Engineering and Service leads at the end of the placement.

Learning Objectives

State what the intern should be able to do by the end of the placement. These should be specific and assessable — they will also form the basis of the mid-point and final review.

• Independently extract, clean and analyse robot fleet telemetry, and present findings that hold up to engineering scrutiny — including correct use of fleet-normalised rates rather than raw counts.

• Plan and run a research session with a non-technical operator end to end (script, consent, observation, synthesis) and defend the resulting prioritisation to stakeholders.

• Produce design artifacts — journey map, wireframe, clickable prototype — that an engineer or designer can act on without further explanation.

• Write a requirement document that separates problem, evidence, scope and acceptance criteria, and states plainly what is not being built.

• Present a data-backed product recommendation to cross-functional leads and handle challenge on method, sample size and assumptions.

• Judge when the available data is good enough to decide and when it is not — and say so.