Data Scientist

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., * 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

• 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, * 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