Senior Applied Data Scientist
Location: London
Department: Global Data Science
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. It’s a chance to apply your expertise to distil complex problems into compelling insights using the best of machine learning and human creativity to deliver effective and impactful solutions for clients. Joining our applied data science team, you’ll investigate, develop, implement and deploy a range of complex applications and components while working alongside super-smart colleagues challenging and rewriting the rules, not just following them.
You will be working on extending and improving dunnhumby’s personalisation propositions and implementing these with Tesco UK. This is an exciting opportunity that will require you to work closely with the Tesco Personalisation team to deliver scalable results at pace. You will be joining a team of 30+ Applied Data Scientists working on Tesco UK.
What we expect from you
- Ability to lead and deliver complex data science and analytical projects end-to-end, from definition to execution.
- Proven experience applying a range of data science techniques to solve real-world business problems.
- Strong proficiency in Python and SQL; experience with PySpark is a plus.
- Hands-on experience working with large-scale transactional datasets (millions of rows).
- A fast learner with the ability to adopt new data science techniques quickly.
- Strong experience designing, evaluating and interpreting controlled experiments (A/B and multi-cell tests), including defining success metrics, guardrails, and statistical significance.
- Confidence in presenting insights and recommendations to both technical and non-technical stakeholders.
- A degree in Computer Science, AI, Machine Learning, Statistics, Maths, Economics, Physics, Engineering, Biology, or a related field is advantageous but not essential.
- Knowledge of the UK retail or consumer goods industry is a bonus.
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)
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