Overview

Data Science Engineer – Behavioural Data & ML – Nottingham (Hybrid, 2 days in office).

This is an opportunity to work on cutting-edge, greenfield AI projects that move beyond research papers and into real-world impact. You’ll design and deploy ML systems that directly improve decision‑making in healthcare, mobility, and retail — making your work both technically challenging and socially meaningful.

You’ll be part of a high-calibre, collaborative team where curiosity is encouraged and ownership is expected. Alongside building production‑grade ML models, you’ll get the chance to grow quickly, shape how AI is applied at scale, and see your work making a real difference.

• 30 days holiday (plus bank holidays) + a no‑questions‑asked wellbeing day
• Equity share options
• Monthly team meet-ups and company socials
• Flexible hybrid working, with a modern office in the heart of Nottingham

The role

• Build and deploy predictive and behavioural ML models used in high‑stakes decision workflows.
• Develop scalable data pipelines for large, messy, real‑world datasets.
• Collaborate with research, engineering, and product teams to deliver explainable, trustworthy AI systems.
• Work with clients and internal stakeholders to ensure models align with business needs.

What we’re looking for

• Strong academic background (STEM, data science, or related).
• ~2+ years’ experience in applied data science / ML engineering (flexible for the right candidate).
• Strong Python and SQL skills.
• Experience building and deploying ML models into production.
• Curiosity, problem‑solving mindset, and drive to work on impactful projects.

This is not just another data role. You’ll be joining a fast‑growing AI company at a pivotal stage, with the chance to shape how behavioural data and ML are used in the real world. If you want ownership, growth, and meaningful impact, this is a rare opportunity.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Information Technology

Industries

Technology, Information and Media, Retail, and Hospitals and Health Care