Data Scientist

Datatech Analytics; Reading; On-site; GBP 55,000 - 75,000; Full time

Job summary

Datatech Analytics in Reading is seeking a Data Scientist to turn data foundations into deployed models that drive real business decisions.

You will work on customer behavior, risk and operational efficiency, building models in Python and partnering with data engineers to productionise features.

The role also involves experimentation, A/B testing, and clear communication of results to senior stakeholders.

Qualifications

• 2–3+ years' commercial Data Science experience.
• Strong statistical fundamentals across regression, classification, clustering, time series and experimental design.
• Strong Python, including pandas, NumPy and scikit-learn.
• Experience of taking models beyond the notebook and into production.
• Understanding of MLOps, CI/CD and model deployment, or experience working closely with engineers.
• A practical approach to modelling, with a preference for explainable solutions over unnecessary complexity.

Responsibilities

• Taking business problems from the initial question through to a deployed model.
• Building and validating models in Python, then monitoring performance once they're live.
• Using statistics, experimentation and A/B testing to properly test ideas.
• Working closely with Data Engineering on pipelines, features and productionisation.
• Going beyond dashboards when the problem needs something more sophisticated.
• Explaining the output clearly to senior stakeholders and keeping the focus on the business answer.

Skills

Python

Statistics

Experimental design

Model deployment

Tools

Pandas

NumPy

scikit-learn

MLOps

CI/CD

Job description

An amazing opportunity for a Data Scientist who wants to build things that actually get used.

The business has spent years getting the data and engineering foundations right. The platform is now in place, and the business is looking for a Data Scientist to help with turning that into models that improve real business decisions.

Think customer behaviour, risk, and operational efficiency. Real problems, real data, and models that make it into production.

What you'll be doing

• Taking business problems from the initial question through to a deployed model
• Building and validating models in Python, then monitoring performance once they're live
• Using statistics, experimentation and A/B testing to properly test ideas
• Working closely with Data Engineering on pipelines, features and productionisation
• Going beyond dashboards when the problem needs something more sophisticated
• Explaining the output clearly to senior stakeholders and keeping the focus on the business answer

What we're looking for

• 2–3+ years' commercial Data Science experience
• Strong statistical fundamentals across regression, classification, clustering, time series and experimental design
• Strong Python, including pandas, NumPy and scikit-learn
• Experience of taking models beyond the notebook and into production
• Understanding of MLOps, CI/CD and model deployment, or experience working closely with engineers
• A practical approach to modelling, with a preference for explainable solutions over unnecessary complexity

Nice to have

• Financial services, fintech or another regulated environment
• MLflow, DVC and Git

The Why

You won't be joining a business that is still trying to work out what to do with its data.

The platform and engineering capability are already there. You'll have an established data team around you who understand Data Science, and genuine scope to help to shape how modelling is used across the business.