Most companies try to meet expectations, dunnhumby exists to defy them. Using big data, deep expertise and AI-driven platforms to decode the 21st century human experience – then redefine it in meaningful and surprising ways that put customers first. Across digital, mobile and retail. For brands like Tesco, Coca-Cola, Procter & Gamble and PepsiCo.
We’re looking for a talented Research Data Scientist who expects more from their career. It’s a chance to extend and improve dunnhumby’s Category Management scientific portfolio. It’s an opportunity to work with a market-leading business to explore new opportunities for us and influence global retailers.
Joining our Data Science team, you’ll work with world class and passionate people to apply machine learning and other data science techniques to business problems, including sales and performance prediction, clustering and community structure, and optimisation. You’ll support our high-performing Category Management experts to translate retail challenges into data science problems, identify creative model implementations to improve performance on complex problems, perform data analysis and model validation, and work with developers to productionise your science. You’ll also have the opportunity to document and present analysis to internal teams and clients.
What we expect from you
Degree or equivalent with a substantial component of mathematics or statistics
Good understanding of machine learning techniques, including regularised regression, clustering, tree-based ensembles, natural language programming and neural networks, with a desire to apply these efficiently to industry problems
An awareness of core statistical and mathematical methodologies concepts. Examples could include statistical inference, probability distributions, confidence intervals, hypothesis tests and optimization.
Ability to prototype solutions using open source software (eg Python, Spark) to facilitate testing of algorithms on large data sets.
Knowledge of, and an ability to apply, design methodologies in order to rigorously evaluate proposed approaches.
Experience with handling large data volumes with modern data processing tools, e.g. by using Hadoop / Spark / SQL Analytical Techniques.
An interest in presenting your work to both technical and non-technical audiences and to contribute to the wider data science community.
It is desirable to have a postgraduate degree or recent relevant experience of conducting research projects, especially in the domains of statistics, market science or machine learning.
Familiarity with coding principles, such as version control and unit tests, and tools such as git would also be beneficial.
What you can expect from us
We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect. Plus, thoughtful perks, like flexible working hours and your birthday off.
You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn.
And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Women’s Network, dh Proud, dh Parent’s & Carer’s, dh One and dh Thrive as the living proof. Everyone’s invited.
Our approach to Flexible Working
At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work.
We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process
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