Machine Learning Scientist - Retail Science at

ASOS is one of the UK’s top fashion and beauty destinations, expanding globally at a rapid pace. Our values are to be authentic, brave and creative, and we live and breathe these in everything we do.
We are looking for Machine Learning Scientists to join ourretail machine learningteam and play a key role in helping ASOS provide the best shopping experience to our millions of customers. The role offers broad exposure to ASOS, requiring close collaboration with retailand technology divisions. You will be part of a highly innovative AI platform working alongside engineers and fellow scientists to solve and productionise interesting and difficult problems and leveraging cutting edge technology. At ASOS, as an online only retailer, we have unique datasets – transactions and click streams for millions of customers and photos, videos, and text descriptions of hundreds of thousands of products.
The ideal candidate will have a strong technical background and experience solving tough problems with large datasets. You will be a highly intelligent self-starter, able to work independently with a strong attention to detail.
  • Working in cross functional team, alongside engineers,business analysts and non-technical stakeholders, creatingnewandimprovinginternal and external facing data products
  • Develop Competitive Pricing models which optimise our Product base across different markets, currencies and fulfilment centres
  • Research and leverage new machine learning and time series prediction methodologies to predict demand and return rates, forecasting future sales of our products
  • Drivingtheimplementationandscale-upofalgorithmsformeasurable impact across the business
  • Keeping up with relevant state-of-the-art research, taking part in reading groups alongside other scientists, with the opportunity to publish novel prototypes for the business at top conferences

We'd love to meet someone with...

  • An advanced degreein Computer Science, Physics, Mathematics or a similar quantitative subject-a a bonus
  • Practical/real world experiences within Demand Forecasting and/or Pricing optimisation
  • Experience in using machine learning methods to solve problems involving complex/high - dimensional data (e.g. image, click - streams, text, video, speech, time series) - This can either be through a distinguished academic career alongsiderelevantpublications, or significant experience solving and productionising models within industry
  • An understanding of the retail, marketing,and/orecommerce industry
  • Comfortable working in a Python data science tech stack (e.g. pandas,NumPy,Dask,scikit-learn,Keras,PySpark,PyTorch). Additional knowledge of Scala is desirable
  • Experience accessing and combining data from multiple sourcesandbuilding data pipelines, including a good knowledge of SQL
  • Understanding of software development lifecycles and engineering practices(Data pipelines, API workflows, CI/CD deployments) alongside ML (DataOps,MLOps)
  • A solid understanding of statistics (hypothesis testing, regressions, random variables, inference)
  • The ability to work collaboratively and proactively in a fast-paced environmentalongside both scientists, engineers and non-technical stakeholders
  • A ‘hackers’ mentality,comfortable using open source technologies.


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