Senior Applied Data Scientist

Posted 5 Days Ago
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London, Greater London, England, GBR
In-Office
Senior level
eCommerce • Retail
The Role
Develop and support complex data science models and applications for retail clients, using statistical modeling, machine learning, Python, SQL, and related technologies. Translate complex business problems into scalable, reusable solutions that generate measurable customer and commercial outcomes. Collaborate with client leadership, define new workstreams, communicate insights to nontechnical stakeholders, and help shape innovative approaches in category management and retail analytics.
Summary Generated by Built In

Senior Applied Data Scientist

 

London | Full-time | Hybrid

 

About dunnhumby

dunnhumby is the global leader in Customer Data Science, helping the world's most ambitious retailers and brands put the customer at the heart of every decision. With nearly 3,000 experts across Europe, Asia, Africa and the Americas, we partner with iconic businesses like Tesco, Coca-Cola, Meijer, Procter & Gamble and Metro to turn data into growth, innovation and measurable value for their customers.

 

Applied Data Science

Our Applied Data Science team turns dunnhumby’s analytical capability into real commercial impact for our clients. Working directly with retailers and brands, we design and deliver the models, algorithms and insights that answer the hardest questions in retail — from personalisation and basket analysis to pricing, promotions and customer loyalty. Every insight we produce is grounded in real customer data and built to make a measurable difference.


About the Role

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 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’re Looking For

  • 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.
  • Comfortable building new workstreams from the ground up, including defining direction, structure, and stakeholder alignment.
  • Background in retail analytics (especially exposure to Category Management) is advantageous.

You'll Thrive If You…

  • Enjoy balancing technical depth with commercial impact.
  • Like exploring new analytical approaches and challenging established thinking.
  • Take ownership of complex problems and see them through to delivery.
  • Are motivated by helping others develop and succeed.

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.


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 your recruiter know what adjustments would help.


UK Benefits

  • Healthcare & Protection: Flexible allowance, private medical insurance through Vitality, life assurance, partner life assurance, income protection and critical illness cover.
  • Pension: Aviva pension scheme with up to 7.5% employer matching.
  • Wellbeing: Access to the Wellness Hub and confidential employee assistance support services.
  • Lifestyle Benefits: Car leasing, Cycle to Work scheme, technology purchase options and additional voluntary benefits.
  • Time Off: 25 days' holiday plus public holidays, option to buy up to 5 additional days, early finish Fridays, loyalty days and a day off for your birthday.
  • Additional Recognition: Long service awards and Talent Scout referral rewards.

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, Mathematics, Physics, Economics, or a related quantitative field
  • Strong programming skills in Python and SQL
  • Experience with version control tools such as Git
  • Solid understanding of analytical technologies, tools, and techniques
  • Excellent logical thinking and problem-solving abilities
  • Strong communication skills, including explaining complex concepts to nontechnical audiences
  • Proven experience in statistical modeling and applying data science solutions to real client problems
  • Ability to connect technical work to customer outcomes and deliver measurable impact
  • Experience building new workstreams, including defining direction, structure, and stakeholder alignment
  • PySpark experience
  • 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.

dunnhumby Insights

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The Company
HQ: London
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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