Data Scientist

Role overview

Working pattern

• Hybrid working, with attendance at the Northampton Head Office 1–2 days per week.

What you will do

• Develop and deploy predictive and prescriptive models, including forecasting, pricing, recommendations, and churn models.
• Build semantic search, RAG, and generative AI workflows to support business decisions.
• Translate challenges from merchant branches and commercial and supply-chain teams into data science deliverables.
• Move prototypes into automated, scalable production pipelines with data engineering and platform teams.
• Create reusable feature stores and reliable, reproducible data assets from enterprise data.
• Create visualizations, dashboards, and narratives that help leaders adopt technical insights.
• Apply governance, GDPR, and AI ethics safeguards, including bias mitigation, transparency, and hallucination controls.

Essential qualifications

• Bachelor’s degree in a quantitative discipline such as computer science, data science, statistics, mathematics, physics, or related STEM field.
• At least 2 years of commercial experience developing and deploying machine learning or statistical models.
• Advanced Python, pandas, NumPy, scikit-learn, and SQL proficiency.
• Knowledge of core ML algorithms, applied AI concepts, Git, code review, and reproducible workflows.
• Ability to connect technical metrics to business outcomes and explain technical concepts clearly to non-technical stakeholders.

Particularly welcome

• Master’s degree or higher in data science, machine learning, or advanced analytics.
• Experience with Google Cloud Platform, MLOps, CI/CD, MLflow, model drift monitoring, retail or supply chain, or production LLMs.
• Google Cloud certifications.

Benefits

• Company or performance-related bonus, savings and purchase schemes, contributory pension, life insurance, private medical insurance, and colleague discounts.