Applied Data Scientist

Reposted 24 Days Ago
Be an Early Applicant
London, Greater London, England, GBR
In-Office
Mid level
eCommerce • Retail
The Role
The Applied Data Scientist will develop and support complex models, apply machine learning techniques, and solve client problems in data science, particularly in category management.
Summary Generated by Built In

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 an 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 Tesco 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, Maths, Physics, Economics or similar field
  • Strong programming skills – Python and SQL are essential
  • Experience with version control tools (e.g. GIT)
  • Solid understanding of analytical technologies, tools, and techniques
  • Logical thinking and problem solving
  • Strong communication skills
  • Experience with and passion for connecting your work directly to the customer experience, making a real and tangible impact
  • Statistical Modelling and experience of applying data science into client problems
  • 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)

Skills Required

  • Degree in Statistics, Maths, Physics, Economics or similar field
  • Strong programming skills - Python and SQL
  • Experience with version control tools (e.g. GIT)
  • Solid understanding of analytical technologies, tools, and techniques
  • Experience with Statistical Modelling
  • Background in retail analytics, especially Category Management

dunnhumby Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about dunnhumby and has not been reviewed or approved by dunnhumby.

  • Fair & Transparent Compensation Pay is considered competitive relative to similar-sized firms in several markets. Positive perceptions of the overall pay-and-benefits mix support the view that compensation is broadly fair.
  • Leave & Time Off Breadth Paid time off is described as generous, with multi‑week starting allowances plus extras like a paid birthday, loyalty‑based additional days, and periodic early Friday finishes. These features contribute to a favorable time‑off experience across several U.S. locations.
  • Healthcare Strength Core coverage includes employer‑verified medical, dental, vision, life, and disability insurance alongside HSA/FSA options. This breadth of coverage is positioned as a solid component of the U.S. package.

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The Company
HQ: London
0 Employees
Year Founded: 1989

What We Do

Dunnhumby is a customer data platform that provides models and insights into how customers engage with retail and e-commerce spaces.

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