Staff Data Analyst (Driver Squad

About HIVED

At HIVED, we’re steamrolling forward as one of Europe’s fastest growing startups, and our momentum shows no signs of slowing.

Based in London, we are a climate and logistics start-up building the first sustainable parcel delivery network at scale, powered by a 100% electric fleet. In an ever-growing industry where unreliable service has long been the norm, HIVED has been built from the ground-up to meet the demands of modern consumers and disrupt parcel delivery. A tech company at heart, our talent and technology is laser-focused on delivering the best possible delivery experience for end-customers and meeting the needs of our retail partners.

From our drivers to our data engineers, we are constantly working to improve this customer experience that makes us deliver better. Already trusted by leading international brands such as John Lewis, Nespresso, Uniqlo, H&M brands and more, we are solidifying our position as the leaders in Europe to tackle this growing market. Our tight-knit team is made up of ex‑Revolut, Bain, Hello Fresh, ASOS, Apple and Google employees, and we are backed by some of Europe’s leading investors and VCs in climate‑tech, logistics and mobility including Planet A Ventures, Maersk Growth, Pale Blue Dot VC, Eka Ventures, Nordic Ninja VC and the British government.

We’re passionate about driving innovation and redefining the future of delivery.

We're looking for a sharp, business‑savvy Staff Data Analyst to drive business outcomes through impactful analytics within the Driver and Deliveries domain. The ideal candidate navigates uncertainty effortlessly and thrives in high ownership environments. They create business impact with the right tool for the job — turning complex analytics into actionable insights, leveraging AI to bring proof‑of‑concept products to life and influencing and collaborating with stakeholders across teams to reach your goal.

We believe in opinionated analytics and creating an edge through intelligent use of technology and data in an industry that has been stuck in its ways for too long - for better or worse. That’s why we empower our growing team of engineers, data and product folks by embedding them in domain‑centered, cross‑functional squads for meaningful business context. We take initiative for impactful projects from day one.

We hone our craft and grow our skills as analytics professionals through functional reporting lines and regular catch‑ups and knowledge sharing sessions across the Data and wider “HIVEDmind” organisation (= Tech + Data + Product + AI&Automations).

In your day‑to‑day you will drive measurable progress through innovative solutions to business problems and identify new opportunities using data analytics. You define the most meaningful KPIs and metrics and help capture them in data models and reports. Being embedded in the Driver Squad, you will work closely with your team mates across Tech and Product to deliver performance and efficiency insights and inform the squad’s roadmap.

Equally, you will collaborate closely with Operations stakeholders beyond your squad to find efficiency gains and opportunities in our data and processes.

The Driver Squad’s mission is to create the industry’s leading delivery operation, identifying and incentivising the best delivery performance across both cost efficiency and delivery quality. You will develop thought leadership across Driver Pay, Driver Performance and Incentivisation and corresponding analytics, identifying opportunities for technological innovation or process improvements and bringing them to life. Your target metrics include delivery success rate, delivery quality, driver retention, unit cost or vehicle utilisation and you only ever consider your job done when your metric has measurably improved.

While this role is focussed mostly on individual contributions, you will also take line management responsibility for 1-2 Analytics (Engineering) professionals within your team. This role reports directly into the VP Data.

• Uncover business and product opportunities through robust…