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Data Scientist (Recommendations Systems)
We’re the UK’s second largest pureplay online retailer and we exist for one simple reason; to make good things easily accessible to more people. It’s our purpose, why we get out of bed in the morning. Today, we turnover more than £1.9bn, our websites get over 1.2m visits every day and 62% of our online sales are from mobile devices. We sell over 1,300 famous brands and deliver 49 million products to over four million customers each year. We’ve got a clear goal. It’s to become a world class digital retailer. We’re already well on the way and, by staying true to our purpose, we believe we’ll achieve our ambition.
About the role
It’s a chance to be part of a multi-disciplinary team, where you’ll collaborate with product and commercial teams to solve our industry’s biggest problems. It’s about gathering, manipulating and analysing some of the largest retail customer datasets in the business.
It involves developing advanced statistical models and building machine learning algorithms. And your focus will be on transforming our data into powerful business insights that keep us pushing the boundaries of digital retail.
Specifically for our recommendations squad we are looking for people who are skilled and up to date with recommendation system methodologies but also with experience in implementing and proving value from them.
You’ll have the opportunity to help shape the data science roadmap in terms of techniques & technical capabilities. We are relatively early in the journey but our ambition is huge and as such you’ll be comfortable
with working within some initial constraints whilst the overall environment evolves.
Likely to be proficient in:
- Big data technology (Spark/Hadoop…..)
- Python, R, Hive
- Relational & non-relational databases
Knowledge and ability to implement recommendation techniques with some real life use cases across utilising item, user and content data.
First and foremost, what we’re looking for is experience in one or more of the following areas: recommendation and optimization algorithms, pricing, experimental design, attribution modelling and/or marketing mix modelling, machine learning, non-linear mixed effect models and linear programming. You might also have significant experience of working with large datasets in retail, e-commerce, or financial services – although this isn’t a requirement.
To join, you’ll need a PhD or MS in a quantitative field such as sciences, statistics or computer science, genuine proficiency in at least one scientific programming language (SAS, Python, R) and a willingness to learn others. Commercial experience is key, so ideally looking for those with between 5 years, ideally with a background of dealing with scalable web, retail & financial data
Intellectually curious, practical, and ready to learn and discover, you’ll be the kind of person who instinctively knows when to work with the results we’ve got or jump in for more analysis.
How to apply
This is a fantastic opportunity for an experienced Data Scientist with Recommendations experience who is looking for their next career move. If you are interested to find out more please contact the Talent Acquisition team at Shop Direct or apply online - or you can reach out to Peter.email@example.com (Talent Acquisition).
Please note that the Talent Acquisition team at Shop Direct is managing this vacancy directly and will not be accepting CVs sent by any recruitment agencies.
Please be advised, if successful in securing this position, you may be required to undertake a credit, CIFAS and CRB check
If you are a current employee of Shop Direct please apply via Talent Online as an internal applicant.
- Annual Bonus
- 30 days holiday + bank holidays + option to buy or sell an additional 5 days
- Matching Pension up to 6%
- Brand Discount up to 25%
- Speke - onsite gym, Costa Coffee, on site cafeteria