Data Scientist

Nicholson Glover; Greater London; Hybrid; GBP 58,500 - 71,500; Full time

Job summary

A leading firm in health and fitness is seeking an experienced Data Scientist to join their team in London. The ideal candidate will take ownership of end-to-end modelling and ML pipeline development, working collaboratively to translate data insights into actions. Strong expertise in Python and SQL, coupled with experience in cloud-based ML workflows, is essential. This role offers a competitive salary of up to £65,000 plus a 10% bonus and allows for hybrid work arrangements.

Qualifications

• Strong technical foundation in Python and SQL.
• Experience with end-to-end predictive models.
• Ability to translate data insights into actionable items.

Responsibilities

• Lead end-to-end modelling and ML pipeline development.
• Work across the full lifecycle from exploration to deployment.
• Shape pricing, retention, and customer insights using data.

Skills

Python

SQL

Cloud-based ML workflows

Commercial communication

MLOps exposure

Tools

Azure ML

CI/CD tools

Model monitoring tools

Job description

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

We’re currently working with one of the UK’s most recognised names in the Health & Fitness industry. They're looking to hire a Data Scientist to join their ambitious and growing team.

The Company

With over a decade of industry presence, this brand has expanded to more than 200 locations across the UK and proudly supports a community of over 500,000 members. They’ve built a reputation not just for their size and scale, but for a people-first culture and strong core values that are truly embedded across the business.

The Role

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

You’ll lead impactful work across the full lifecycle — from exploration and predictive modelling to deployment and automation — using modern cloud tooling to shape smarter pricing, retention, and customer insight.

Key attributes of the suitable Data Scientist include:

• Strong technical foundation in Python, SQL, and cloud-based ML workflows, with experience building and deploying end-to-end predictive models.
• Commercially minded communicator who can translate data into clear, actionable insight and work collaboratively with technical and non-technical stakeholders.
• Exposure to MLOps or ML engineering practices, including pipelines, CI/CD, model monitoring, and working with tools like Azure ML or Fabric. (Desired, not mandatory)