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Permanent

Data Scientist - Modelling & Intelligence

London
money-bag £60000 - £69000/annum
225069494
Posted 1 week ago

Data Scientist- Modelling & Intelligence - London
London Hybrid (3 days in the office, 2 days from home)
6 month Fixed Term Contract
Salary to -69,000 pro rata experience dependent
Ref: J13096

What if modelling actually sat at the centre of business decisions, not just reporting?

We''re working with a leading independent property consultancy, building out a new analytics capability, where modelling is becoming central to how the business operates.
This isn''t a reporting role. It''s focused on exploring data and solving real problems. Recent work has included:

-Clustering complex datasets
-Modelling trends to support commercial decisions
-Understanding patterns and behaviours across large datasets

You''ll work closely with stakeholders to shape problems, build models and turn analysis into something people can actually use. Python is key, with a strong focus on modelling and thinking rather than tooling.
We''re looking for someone who is comfortable working with messy data, enjoys problem solving and can communicate clearly with non technical stakeholders.

What you''ll bring
-Strong Python and SQL
-Advanced modelling capability
-Experience working with complex datasets
-Strong communication and stakeholder engagement
-Experience working with spatial and non spatial data desirable
-Exposure to Azure or Databricks beneficial
-Degree in a quantitative field, MSc or higher beneficial

It''s an opportunity to join a team that is still taking shape, with real influence over how data is used going forward.

Get in touch to learn more.

Please note that applicants must have the right to work in the UK. Sponsorship is not available for this opportunity.


Alternatively, you can refer a friend or colleague by taking part in our referral scheme. For each relevant candidate you introduce and we place, you will be entitled to our reward scheme.

Datatech is one of the UK''s leading recruitment agencies in analytics and the host of Women in Data. For more information, visit (url removed) .



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