Data Science Engineer

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 Data Science Engineer who expects more from their career. It’s a chance to extend and improve dunnhumby’s world class science capabilities. It’s an opportunity to work with a market-leading business to explore new opportunities for us and influence global retailers.

Joining our Customer Data Science team, you’ll work with world class and passionate people to create reusable science modules, ensuring they are productionised, robust and available to the business. You’ll contribute to the research and implementation of new approaches to address complex problems, and explore changes to process and tooling to enable research at scale.

What we expect from you

· Experience building analytical python solutions, installable with pip/conda

· Experience working with relational databases, and SQL-like operations

· Experience processing big data, ideally in a Hadoop/Spark environment, would be highly beneficial

· Understanding of Continuous Integration/Continuous Delivery (CI/CD) & DevOps processes, and experience applying them within an Agile framework is beneficial

· Understanding of machine learning techniques such as regularised regression, clustering or tree-based ensembles would be an added advantage

As a Data Science Engineer in Customer Data Science your main roles will be to:

· Develop and support standalone, reusable python packages that surface novel data science solutions, and are fundamental to best-in-class, global products

· Build processes and tools to support the research of global science methods, including visual dashboards to showcase their approaches

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)