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Data Scientist (Health & Fitness)

Nicholson Glover

Location

London Area, United Kingdom

Salary

Not specified

Type

fulltime

Posted

Today

via linkedin

Job Description

Data Scientist \| Health \& Fitness \| London / Hybrid \| Up to £65,000 DOE \+ 10% Bonus

We’re currently partnering with one of the UK’s most recognised brands in the Health \& Fitness sector. They’re looking to hire a Data Scientist to join their ambitious and growing data team.

The Company

With over a decade of industry presence, this brand has grown to more than 200 locations across the UK and supports a thriving community of over 500,000 members. They’ve built a reputation not only for their scale and success, but for a genuinely people-first culture and strong core values that are embedded throughout the organisation.

The Role

This is an exciting opportunity for a commercially minded Data Scientist to take ownership of end-to-end modelling within a fast-paced, consumer-focused business.

You’ll work across the full data science lifecycle — from exploratory analysis and predictive modelling through to deployment and automation — leveraging modern cloud-based tooling to drive smarter decisions around pricing, retention, and customer engagement. This is a commercially focused Data Science role with a strong Marketing and Customer lens, with projects spanning customer acquisition, retention, portfolio performance, and wider commercial optimisation.

The Candidate

Key attributes of the suitable Data Scientist include:

  • Technical modelling expertise

– Strong technical foundation in Python and SQL, with experience developing and deploying end-to-end predictive models.

  • Commercial communication skills

– A commercially minded communicator who can translate complex data into clear, actionable insights and collaborate effectively with both technical and non-technical stakeholders (ideally with experience supporting commercial or marketing-focused projects).

  • Econometrics / MMM experience (desirable

) – Ideally, experience working on Media Mix Modelling (MMM) or similar econometric or statistical modelling approaches.

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