Senior Research Data Scientist

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profile Job Location:

London - UK

profile Monthly Salary: Not Disclosed
Posted on: 8 hours ago
Vacancies: 1 Vacancy

Job Summary

dunnhumby is the global leader in Customer Data Science partnering with the worlds 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 2500 experts in offices throughout Europe Asia Africa and the Americas working for transformative iconic brands such as Tesco Coca-Cola Nestlé Unileverand Metro.

Were looking for a talented Senior Research Data Scientist who expects more from their career. Its a chance to extend and improve dunnhumbys world class science capabilities. Its an opportunity to work with a market-leading business to explore new opportunities for us and influence global retailers and suppliers.

Joining our team youll work with world class and passionate people to apply machine learning and statistical techniques to business problems. Youll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. Youll have the opportunity to present results to a variety of internal stakeholders and will apply these techniques and algorithms to create dunnhumby science solutions that can be delivered across our clients and engineered into science modules.

This role will be focussed across insight automation and product assortment with applications of science including identifying new and growing product needs optimising the mix of products predicting the impact of changes product attribute generation and applications of generative AI for product support and insights.

What youll be doing:

  • Create new science-based solutions that can be captured as science modules and applied across clients with support from senior team members.
  • Pick up new machine learning approaches such as regularised regression clustering or tree-based ensembles graph-based approaches natural language processing and neural network techniques and apply them on client data.
  • Perform exploratory data analysis to characterise and visualise datasets
  • Extend and develop programming skills in languages such as Python and Spark to develop efficient science code for science modules.
  • Help identify new opportunities within the Data Science space for future dunnhumby solutions.
  • Implement advice from colleagues to resolve challenges.
  • Follow Quality Assurance processes ways of working and meet coding standards.
  • Ensure smooth running of your projects working with senior team members for direction.
  • Build strong relationships within the team and with internal stakeholders ensuring clear and effective communication.

Who youll get to work with:

  • Within dunnhumby youll primarily work with
  • Applied and Research Data Scientist teams
  • Data Science Engineering teams
  • Product and Client teams where required

What youll need:

  • Masters degree or equivalent in Computer Science Artificial Intelligence Machine Learning Statistics Applied Statistics Physics Engineering Biology or related field.
  • Experience with machine learning techniques such asregularised regression clustering or tree-based ensembles and the ability to implement them through libraries.
  • Experience with programming ideally Python and the ability to quickly pick up handling large data volumes with modern data processing tools e.g. by using Hadoop / Spark / SQL
  • Experience with or ability to quickly learn open-source software including machine learning packages such as Pandas and scikit-learn along with data visualisation technologies.
  • A willingness to present your work to both technical and non-technical audience and to contribute to the wider data science community.


A plus if you also have:

  • PhD in Computer Science Artificial Intelligence Machine Learning Statistics Applied Statistics Physics Engineering Biology or related field.
  • Experience in retail sector.

What you can expect from us

We wont just meet your expectations. Well defy them. So youll enjoy the comprehensive rewards package youd 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.

Youll 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 dont 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)


Required Experience:

Senior IC

dunnhumby is the global leader in Customer Data Science partnering with the worlds 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 valu...
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Global leader in Customer data science, retail media and analytics, experts in working with brands, grocery retail, retail pharmacy, and retailer financial services.

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