Production Data Scientist: Turn Models into Real Impact

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

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.