dunnhumby is the global leader in Customer Data Science, partnering with the world's most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers.

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, Nestlé, Unilever and Metro.

We're looking for a Senior Applied Data Scientist who expects more from their career. This is an opportunity to apply your expertise to distil complex problems into meaningful, actionable insights -leveraging world-first science, cutting-edge machine learning techniques and human creativity to deliver impactful solutions for clients.

Joining our advanced data science team, you'll be responsible for the ongoing implementation, support and development of complex models and applications, working alongside exceptionally talented colleagues who are challenging and rewriting the rules rather than simply following them.

Our team works closely with retailers to solve some of the most interesting and challenging problems in the category management space. We work collaboratively with our client leadership team and with our clients, to build solutions that are re-usable, scalable and deliver measurable value. You'll drive change, shape innovative solutions, and actively redefine how organizations harness data.

What we expect from you

• Degree in Statistics, Mathematics, Physics, Economics, or a related quantitative field
• Strong programming skills - Python and SQL are essential; PySpark experience is highly advantageous
• Experience with version control tools (e.g. GIT)
• Solid understanding of analytical technologies, tools, and techniques
• Excellent logical thinking and problem solving abilities
• Strong communication skills, with the ability to explain complex concepts clearly to non technical audiences
• Proven experience in statistical modelling and applying data science solutions to real client problems
• A passion for connecting technical work to real customer outcomes, delivering clear and measurable impact
• Effective stakeholder management and the ability to build trusted relationships across teams
• Project Management and/or Team Leadership experience
• Background in retail analytics (especially exposure to Category Management) is advantageous

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, dh Enabled 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.

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)