Data Scientist

BENEFITS – Bonus, Pension, Private Healthcare, Hybrid Working, Learning & Development Budget, Flexi-time, Career Progression etc.

We are a growing, data-driven organisation where analytics and machine learning are central to improving customer engagement, operational efficiency, and commercial performance. As we continue to invest in our data capability, we are looking to appoint a Data Scientist to help develop innovative, production-ready machine learning and AI solutions.

We are looking to hire a commercially minded Data Scientist to take ownership of the complete data science lifecycle, from problem definition and experimentation through to production deployment. You will work with large-scale transactional and behavioural datasets, partnering with stakeholders across the business to deliver measurable commercial impact through data.

The Data Scientist MUST have:

Commercial experience delivering end-to-end Data Science and Machine Learning solutions

Strong programming skills in Python, including pandas, NumPy, and Scikit-learn

Excellent SQL skills and experience manipulating large datasets

Experience building predictive models including classification, regression, forecasting, or anomaly detection

Strong understanding of statistics, hypothesis testing, and experimental design

Experience designing and analysing A/B tests and controlled experiments

Experience deploying machine learning models into production environments

Excellent stakeholder management and communication skills with the ability to explain technical concepts to non-technical audiences

The Data Scientist will ideally have the following attributes:

Experience working with cloud platforms such as Azure, AWS, or GCP

Experience building reproducible machine learning pipelines using Git and modern software development practices

Knowledge of data visualisation tools such as Power BI, Tableau, or similar

Experience with Azure Machine Learning or equivalent cloud ML platforms would be beneficial

Experience developing time-series forecasting models

Knowledge of feature engineering techniques for large-scale transactional datasets

Familiarity with MLOps, model monitoring, and production AI systems

Exposure to Generative AI, Large Language Models (LLMs), or Agentic AI applications would be advantageous

Experience with OCR, document processing, or intelligent automation would be beneficial

Knowledge of tools such as Streamlit, MLflow, or similar would be advantageous

A proactive mindset with a passion for solving complex business problems using data

The Data Scientist role will involve:

Designing, developing, and deploying production-ready machine learning models to solve commercial challenges

Building classification, segmentation, forecasting, anomaly detection, and predictive models

Designing, executing, and analysing A/B tests and statistical experiments

Engineering robust feature pipelines from large transactional and behavioural datasets

Taking models from prototype through validation, deployment, monitoring, and optimisationli>

Developing reusable, version-controlled machine learning pipelines following engineering best practices

Creating dashboards and visualisations to communicate analytical findings to business stakeholders

Collaborating with commercial, product, and operational teams to identify data-driven opportunities

Contributing to the development of AI-enabled products, including Generative AI applications where appropriate

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