dunnhumby is the global leader in Customer Data Science, empowering businesses everywhere to compete and thrive in the modern data-driven economy. We always put the Customer First.

Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail – one of the world’s most competitive markets, with a deluge of multi-dimensional data – dunnhumby today enables businesses all over the world, across industries, to be Customer First.

dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Meijer, Procter & Gamble and Metro.

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 Price & Promotions scientific portfolio. Joining our Price & Promotion Science team, you’ll predominantly work on the designing and building of dunnhumby’s world class advanced demand forecasting models. It’s an opportunity to work with a market-leading business and influence global retailers.

You will also work alongside passionate and expert people to apply machine learning, statistical, and econometric methods to a range of other customer data science problems. You’ll have the opportunity to present your work to both internal teams and clients.

What we expect from you

· Exceptionally strong mathematical and statistical skills.

· Passion about designing predictive models from first principles whenever possible.

· Pragmatic approach to modelling, balancing theoretical validity and practical use.

· Good working knowledge of any of: Maximum likelihood inference, mixed effects models, hierarchical models, Bayesian inference.

If the above points resonate with you, it is also likely that you will have:

· A degree or equivalent in a statistical or mathematical subject.

· A postgraduate degree or recent relevant experience of conducting research or mathematical analysis, especially in the domains of statistics, physics, econometrics, or machine learning.

· Ability to prototype solutions using e.g. Python, R, or MATLAB, to facilitate testing of algorithms on large data sets.

· Good understanding of machine learning techniques, with applications to classification, regression, and clustering.

· Working knowledge of databases and SQL

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 Gender Equality Network, dh Proud, dh Family, dh One and dh Thrive as the living proof.  We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you. For an informal and confidential chat please contact stephanie.winson@dunnhumby.com to discuss how we can meet your needs. 

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.

For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here)