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Senior Data Scientist

Ruby Magpie
London
1 week ago
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Data Scientist – Quantitative

Hybrid (3 days in London office) | Full-time | Permanent

You need to have a core background in statistical analysis of survey data and experience of working in a research agency.


An exciting opportunity has opened up at a fast-growing insight and strategy consultancy for an experienced Data Scientist to lead the development of their in-house data science capabilities. This is a newly created role where you'll shape the future of how the team integrates advanced analytics, diverse datasets, and machine learning into high-impact client projects across sectors such as media, tech, and entertainment.


You’ll be joining a collaborative, supportive environment with around 60 consultants, strategists, and analysts – all passionate about delivering actionable insight and tackling complex questions. The consultancy is known for its bespoke, high-quality approach and is now expanding into deeper data-led offerings.


The Role

This is a hands-on, strategic position reporting into a senior leader within the Quant team. You'll work across a mix of project delivery, innovation, and team development – helping shape everything from statistical capability to the company’s broader data vision.


You’ll work on:

  • Advanced analytics projects (segmentation, conjoint, MaxDiff, KDA, etc.)
  • Processing large, complex datasets (e.g. transactional data, 1st-party data, behavioural)
  • Developing infrastructure and tooling for scalable analysis
  • Expanding the use of AI, synthetic data and machine learning
  • Collaborating with marketing to shape new, data-led propositions
  • Upskilling team members in data science and statistical thinking
  • Representing the agency externally in thought-leadership or event settings (optional)


What You’ll Need

  • 5+ years of data science experience, ideally with at least 2 years working with survey or behavioural data, ideally in a consultancy or agency environment
  • Strong command of quantitative analysis methods, including regression, segmentation and more advanced statistical techniques
  • Proficiency in tools like Python, SQL, SPSS, Q or R
  • Confidence working with and integrating non-survey data sources such as 1st-party or behavioural data
  • Ability to explain technical findings clearly to non-technical audiences
  • An innovative and proactive mindset with a love of new ideas, tools, and learning


Nice to Have

  • Experience establishing data science workflows in a commercial setting
  • A track record of upskilling or training others in data/statistics
  • A desire to contribute to external thought leadership (e.g. presenting at events)


What’s On Offer

Competitive salary and benefits

Would also consider someone on 4 days a week

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