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Lead Data Scientist – Retailer
Salary: Competative plus 20% bonus
Location: 1-2 days in London office pw
Looking to scale and build on their already established digital and data science community, this national retailer has multiple roles available at this level within the following teams:
Loyalty & Personalisation
Working on data science projects and building models, productionising these at scale for deployment across the business. With millions of customer records being generated from the loyalty card, you will exploit existing machine learning models, aiming to add more value in loyalty, looking at the data in new ways and building new user cases (emotional drivers for loyalty, for example). Techniques employed include causal inference (separating the causation and correlation in the analysis, really working to understand the reasons behind customer behaviour),linear programming and A LOT of optimisation.
The manager for this team holds a Phd from Oxford, bringing a combination of academic research experience as well as significant exposure in the land of start and scale ups.
The culture is friendly, ambitious and ‘non-traditional retail’ in terms of ways of working – Agile, innovative and forward thinking!
Led by another impressive Phd graduate with experience from management consultancy and start ups… you are in very good hands! This team are responsible for massively impactful projects, where millions of pounds are at stake and the wins are big – truly greenfield projects which have never been done before.
With frequent hackathons, you’ll work collaboratively on projects such as building computer vision models which can recognize the physical set up of stores (tidiness, product positioning) to people and their movements and interactions around stores too.
Your work has impact on physical and tangible objects, which gives it a really unique feel in comparison to other data science projects you might have worked on before. The projects are broad and business wide, so there is always variety.
This team is led by a Phd grad with roots in Psychology and Statistics. There are also two work streams within this team: Recommenders & Category Growth Decisioning & In House Marketing Comms System
Skills & experience required: