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# Data Scientist

- **Company:** Datatech Analytics
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £75,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Computing, Customer Data Management, Python (Programming Language), Machine Learning, Software Deployment, SQL Databases, Feature Engineering, Model Validation, Jupyter, Machine Learning Operations
- **Published:** October 13, 2026
- **Apply:** https://datatech.org.uk/job/senior-data-scientist-61130732/?form=apply#wpjb-scroll

## About the Role

* 4-5 years' experience in data science or advanced analytics.
 * Strong mathematical, statistical or physics background.
 * Experience analysing large volumes of first-party customer data, ideally within an agency, retail or insurance environment.
 * Strong Python, SQL and Jupyter skills.
 * Hands-on experience with customer segmentation, propensity modelling and forecasting.
 * Proven ability to deliver end-to-end machine learning projects, from analysis through to deployment.
 * Commercially minded, with strong communication and stakeholder management skills.

Experience in a consultancy or agency environment would be advantageous. Cloud experience is welcome, but no specific platform is required.

## Description

Build AI-powered products that turn customer data into commercial impact.
Join an established analytics and technology business developing cutting-edge SaaS products and bespoke AI solutions for major brands across retail, finance, travel, telecoms and healthcare.
With two live products and further AI solutions in development, this is an opportunity to work on applied data science that delivers tangible business results.

The Role
Reporting to the CTO, you'll own end-to-end data science projects, developing and deploying machine learning models that drive better customer and commercial outcomes.

You'll work across:

 * Customer segmentation, propensity modelling and churn prediction.
 * Revenue and demand forecasting.
 * Python-based modelling, feature engineering and model validation.
 * Production deployment, cloud infrastructure and MLOps.
 * Translating complex analysis into actionable commercial insights.
 * Collaborating with product, engineering and client teams to develop AI-powered solutions.