Data Scientist, Recommendations

At Thread we’ve set out to rethink clothes shopping for the digital age. By combining expert stylists, machine learning algorithms and a marketplace with one of the largest fashion ranges in the world we’ve created a truly unique online platform that gives everyone a highly personalised selection of the perfect clothes just for them – in their size, budget and taste.   It’s your own personal clothes store. 

Over 1 million people and counting use Thread. We’ve recently launched womenswear which is growing faster than our menswear business and, for 25% of our customers, we’ve become the only way they shop. 

There’s a $10bn+ opportunity globally to build the Spotify of retail, and we’re leading the way. We believe having an intelligent assistant in your pocket is how the majority of people will shop in the future, and we’re looking for a talented Data Scientist who wants to help millions of people discover its value.

The role

We’re looking for a Data Scientist to work on Thread’s key Machine Learning recommendation models. You’ll work to improve and iterate our personalisation algorithms which are core to our product, so that we can serve high quality AI-driven clothing recommendations to men and women in the UK and internationally.

You’ll work on improving the quality of the personalised clothing suggestions we make to our users, through research & implementation of new features, modeling techniques and optimisations. You will assist with the analysis and understanding of recommendation performance and evaluate opportunities for major UX improvements through better personalisation.
The role will report into and work closely with our Head of Data Science, Ed Snelson, and also work cross-functionally as part of our wider Product team alongside our talented product designers, product managers, frontend & backend developers.

What you’ll be doing:

  • Developing and improving ML recommendation models:
  • Identifying key areas of opportunity from a UX perspective
  • Research into data we could be using or collecting, but are not yet
  • Modelling data using a variety of modelling techniques including linear models, trees, neural nets, reinforcement learning, embeddings etc.
  • Implementing & deploying model & algorithm improvements live in production
  • Working on model explainability and implementing algorithm “guardrails”
  • Analysis & understanding of recommendation performance
  • Understanding & monitoring changes of performance of the recommendations system as a whole and how the different parts of the system contribute
  • Understanding & analysis of long-term feedback loops e.g. how to balance exploration & exploitation
  • Working closely with our stylists & merchandisers as part of our cross-functional recommendations team
  • How does our clothing range best support our recommendations?
  • Which styles should we be investing into in the coming season?

You may be a fit for this role if you…

  • Have a passion for working on ML models in a production environment with a direct and major impact on core UX
  • Have a range of experience working with different types of ML modelling techniques
  • Have worked closely with engineers to get ML models running in production
  • Have a good level of python experience & craft which enables self-sufficient work within the “template” of our existing model training & live production setup
  • Have familiarity & experience with production engineering tools & processes: Git, CI/CD tools, code-review, testing
  • Care deeply about the craft and quality of your work, whilst at the same time being pragmatic and excited by working in a fast-paced startup environment and the trade-offs that entails
  • Experience in industry as an ML practitioner

Talented Data Scientists can work anywhere, so why choose us?

  • Opportunity to become recognised as one of the leaders in your field through playing a key role in the future growth of a high-profile startup
  • Be part of a values-led team who are working hard to create one of the highest quality cultures in the world. Learn more about what we’re trying to do in our culture deck. Informal, non-hierarchical, non-political, sociable work environment with lots of autonomy and independence
  • Gain first-hand experience of how to start, grow, market and raise funding for startups (perhaps useful for your own company one day)
  • Flexible working 
  • We believe in measuring outputs/results as opposed to inputs like hours worked or holiday days taken. As such, we have an unlimited holiday policy. This means you can take as much or as little time off as you feel you need to operate at peak productivity
  • A competitive salary and a generous equity stake in the company (you’re working hard to make the company successful, so we believe you should share generously in the reward!)

We’re currently working remotely as a team. We’re planning to gradually return to the office later in the year in line with government guidance - the safety and wellbeing of our team is our number one priority. Long-term, this role will be based out of our Aldgate, London office, with flexible working arrangements.


If this role sounds exciting to you, please apply below. If you’re unsure, please still get in touch—we welcome applicants from different backgrounds and would love to hear from you.