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 causal inference and statistics, to join our cross-functional Marketing Effectiveness team. Our Marketing Effectiveness team plays a key role helping ASOS provide the best shopping experience to millions of customers, using techniques such as incrementality testing and media mix modelling to understand,  measure and optimise marketing spend. The role offers broad exposure to ASOS, requiring close collaboration with retail, marketing and technology divisions. 

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.  

Key Responsibilities:  

• Driving the technical development and improvements of our geo-experimentation product used to model incremental uplift of ASOS’ digital spend, and our media mix modelling capability that supports long-term media planning.  
• 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 using causal inference techniques. Ideally with experience of developing geo-experimentation frameworks, and/or MMM models that have been used to measure the impact of digital media spend. 
• 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