Quantitative Data Scientist

The Opportunity Hub UK Ltd; Nottingham; Hybrid; GBP 44,000 - 57,000; Full time

Benefits offered by this job

Hybrid work from Nottingham office

Private medical insurance and pension

Generous annual leave and structured进

Job summary

The Opportunity Hub UK Ltd in Nottingham is seeking a Quantitative Data Scientist to turn messy, high-volume data into deployable models for AI & Technology products.

You’ll build and validate models, structure datasets, and design experiments. You’ll work with engineers to productionize models and communicate results to non-technical stakeholders.

Qualifications

• Strong grounding in statistics, probability and applied machine learning.
• Proficient Python for data work (pandas, scikit-learn).
• Several years’ experience as a Quantitative Data Scientist or similar.
• Ability to explain technical findings to non-technical stakeholders.

Responsibilities

• Build and validate statistical and ML models that feed live AI products.
• Clean, structure and interrogate large datasets to find actionable patterns.
• Design experiments (A/B tests, causal inference) and report results clearly to non-technical stakeholders.
• Work with engineers to get models into production and monitor performance.
• Write clear documentation so others can pick up and audit your work.
• Monitor upstream data quality and flag issues proactively.

Skills

Statistics

Python

Machine Learning

Communication

A/B Testing

Education

Bachelor's in a quantitative field

Tools

Python

PyTorch

TensorFlow

Job description

Perfect role for a mid professional looking to grow their AI & Technology career in Nottingham.

AI-driven products live or die on the quality of the data behind them. This growing technology company, an established SME with a reputation for solid engineering, needs a Quantitative Data Scientist who can turn messy, high-volume data into models that actually ship. It's a chance to work close to the product, not buried three layers away from it.

Here’s what you’ll be doing:

Build and validate statistical and machine learning models that feed directly into live AI & Technology products

Clean, structure and interrogate large datasets to find patterns the business can act on

Design experiments (A/B tests, causal inference studies) and report results in plain English to non-technical stakeholders

Work with engineers to get models into production, then monitor how they perform once they’re live

Write clear documentation so your work can be picked up, audited and improved by others

Keep an eye on data quality upstream, flagging issues before they become someone else’s problem

Here are the skills you’ll need:

Solid grounding in statistics, probability and applied machine learning, not just theory

Strong Python (pandas, scikit-learn, and ideally some exposure to PyTorch or TensorFlow)

A few years’ experience as a Quantitative Data Scientist or similar, with evidence of models that made it past a notebook

Able to explain a technical finding to someone who doesn’t want the maths, just the answer

Curious by default. The best people in this role ask “does this actually hold up” before they ship anything

Key perks and benefits:

£43,500 to £56,500 depending on experience, plus a bonus scheme

Hybrid working from the Nottingham office, with genuine flexibility around how that's split

Private medical insurance and a proper pension contribution

Generous annual leave, structured progression, and a company that’s past the chaotic early-stage phase without losing its pace

Why pursue a career in AI & Technology?

AI & Technology is one of the few sectors where demand for good quantitative people has consistently outpaced supply, and that gap isn’t closing soon. Nottingham has quietly built a strong cluster of technology employers outside London, which means Quantitative Data Scientist roles here often come with less competition and more room to actually influence the product. Get a few years of solid, varied work under your belt in this field and the career options tend to open up fast.