Senior Data Scientist

HIVED is the first fully electric delivery company designed for the ecommerce market. With our purpose-built technology, commitment to an exceptional delivery experience, and sustainability-as-standard approach, HIVED is setting a new delivery standard for retailers and consumers.

HIVED has already delivered millions of parcels across London for the biggest brands including ASOS, Uniqlo, Nespresso and Zara. Backed by leading Investors such as Maersk Growth, Pale Blue Dot and Planet A Ventures, HIVED is at the forefront of sustainable, scalable logistics solutions.

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, HelloFresh, ASOS, Apple and Google employees, and we are backed by some of Europe’s leading investors and VCs in climate-tech, logistics and mobility includingPlanet A Ventures,Maersk Growth,Pale Blue Dot VC,Eka Venturesand the British government. We’re passionate about driving innovation and redefining the future of delivery.
   

Role Overview 📝

We are looking for an experienced and ambitiousSenior Data Scientistto join our team. Our ideal future colleague loves diving deeply into complex logistics challenges, real-world problems and pushing the envelope of what’s possible. They get excited as much about creating tangible business impact and improving the delivery experience of millions of recipients and delivery drivers as they enjoy evaluating and crafting just the right ML model for their use case.

Data at HIVED 📊

We believe in staying ahead and creating a competitive edge through intelligent use of data in an industry that has been stuck in its ways for too long. That’s why we empower our Data team and embed them in product-centered, cross-functional squads for meaningful business context and encourage taking the initiative for impactful projects from day one. We hone our craft and grow our skills as data professionals through functional reporting lines and regular catch-ups as well as knowledge sharing sessions across the Data and wider HIVEDmind organisation (Tech + Data + Product).
 

Your day-to-day 🔄

Your day-to-day activities will range from ideating novel solutions to business problems with your squad and fellow business users, to creating meaningful experiments and developing, deploying, monitoring and maintaining machine learning models that move the needle.

You will work alongside data analysts, data engineers, routing and backend engineers and product managers to develop meaningful products and bring your solutions to live. Wherever you see an opportunity, you will contribute to developing and growing our machine learning platform through selecting the right tooling, setting standards and defining best practices.

What you might work on:

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• Routing and ETA calculations: improving our model of the real world to power our daily deliveries, creating reliable recipient experiences and increasing operational resilience
  
• Address intelligence: solving the most complex challenge in the life of a delivery driver — reliably locating the exact delivery location and navigating the “last meter” efficiently
  
• Parcel volume forecasting and shift scheduling optimisation
  
• National expansion modelling and optimising our physical network structure
  

Responsibilities 📋

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• Take initiative and translate business context and problem statements into impactful data solutions
  
• Develop powerful machine learning models, analyses and experiments
  
• Collaborate with fellow squad members to deploy your solutions and monitor their performance and impact
  
• Evolve our ML and data platform, select the right tooling and set standards for a growing team
  

Your profile 👤

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• 4+ years of experience in a similar data science or analytics role
  
• Degree with strong statistical/ mathematical component (e.g. Maths, Statistics, Data Science, Artificial Intelligence, Operations Research or equivalent)
  
• Proven track record of delivering high-impact machine learning models and developing algorithms that solve real-world challenges
  
• Experience programming in Python, SQL and using ML platforms and frameworks such as Sagemaker, MLflow, Seldon Core or similar
  
• Prior experience or interest in working with geospatial data
  

Technologies we use 🛠️

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• Programming languages: SQL, Python, LookML, (+ Go for other backend services)
  
• Development tools and frameworks: dbt, dagster, Airbyte, dlt, data-diff, Elementary
  
• Data lake and warehouse: GCS, BigQuery
  
• Analytics: Looker, Looker Studio and geospatial analytics tools
  

How we reward our team 🎁

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• Dynamic working environment with a diverse and driven team
  
• Huge opportunity for learning in a high-growth environment, with progression opportunities based on success in the role
  
• 25 days of holiday allowance plus public holidays
  
• Wellbeing initiatives, including three wellbeing days in addition to holiday allowance
  
• Weekly team lunch and regular company socials
  
• MacBook Air or Windows Laptop (depending on your preference)
  
• Hybrid working set-up with in-person time expected at our Shoreditch office
  
• Enhanced maternity/paternity/adoption policy