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A leading online fashion retailer is seeking a Senior Applied Scientist to join their Marketing Effectiveness team in London. The role involves utilizing causal inference and statistics to optimize marketing spend, collaborating with various departments, and mentoring junior team members. Candidates should have experience in Python, machine learning, and ideally, the ecommerce industry. This position offers a flexible work environment and various employee benefits including discounts and development opportunities.
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.