Senior Applied Scientist - Recommendations

We’re ASOS, the online retailer for fashion lovers all around the world.

We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions.

But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list.

Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you.

We are looking for a Senior Applied Scientist, with expertise in deep learning, to join our cross-functional Search and Recommendations team to help further the success of our recommender system. Our system plays a key role in helping ASOS provide the best shopping experience to our millions of customers by surfacing the right product to the right customer at the right time, handling up to 8000 requests per second at peak in production.  The whole team is responsible for the end-to-end system, and we are all accountable for making sure it performs in production, at the scale at which ASOS operates. 

The role sits within the Applied Science domain, which is responsible for the algorithms that power ASOS digital ecosystem. From Recommender Systems through to forecasting models that drive key operating decisions, the teams maintain, build and innovate in some of the most interesting areas of machine learning at scale, training models on unique datasets, transactions and clickstream data. 

What you’ll be doing: 

• You will be part of an agile, cross-functional team building and managing a large-scale recommender system, working with massive amounts of data, and delivering deep learning models into production.  
• You will be driving the implementation and scale-up of algorithms for measurable impact across the business and set up and conduct large-scale experiments to test hypotheses and drive product development. 
• You will be keeping up to date 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. 
• You will be continually developing and improving our code and technology, taking an active role in the conception of brand-new features for our millions of global customers.  
• You will be mentoring and coaching junior members of the team, supporting their technical progress. 
• You will take part in regular Tech Develops days to learn new things, take part in internal and external hackathons, and share your knowledge and help drive improvements in science and engineering. 
• You will support our culture by championing Diversity, Equity & Inclusion strategies. 

About You

• You are an experienced Applied Scientist with hands on experience of building recommender systems or a track record of using state of the art deep learning methods to solve complex business problems
• Will have some knowledge or experience of working in retail, marketing, or the ecommerce industry. You thrive in working in a cross-functional platform, including scientists, engineers, and non-technical stakeholders.
• You are comfortable working in Python software stacks and familiar with at least one deep learning framework (such as TensorFlow/Keras and PyTorch) and enjoy going from ideas and prototypes into products and applications.  
• You have a solid understanding of software development lifecycles and engineering practices, alongside a good understanding of ML and statistics.  
• You will be comfortable providing technical leadership, mentoring, and coaching to a motivated development team. 
• We would love to meet someone who has authored publications in top-tier machine learning conferences or journals (such as NeurIPS, ICLR, ICML, KDD, CVPR, ICCV, ECCV, ACL, EMNLP) and want to keep up to date with the state of the art. 

BeneFITS’

• Employee discount (hello ASOS discount!)
• ASOS Develops (personal development opportunities across the business)
• Employee sample sales
• Access to a huge range of LinkedIn learning materials
• 25 days paid annual leave + an extra celebration day for a special moment
• Discretionary bonus scheme
• Private medical care scheme
• Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits

Why take our word for it? Search #InsideASOS on our socials to see what life at ASOS is like.

Want to find out how we’re tech powered? Check out the ASOS Tech Podcast here https://open.spotify.com/show/6rT4V6N9C7pAXcX60kzzxo . Prefer reading? Check out our ASOS Tech Blog here https://medium.com/asos-techblog.