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