Senior Data Scientist

Overview

In this role you will lead the technical development of models and data pipelines to personalise customer experiences and optimise offer decisioning at scale. You will work within the Data & Analytics ecosystem to drive commercial value and customer loyalty, collaborating with cross-functional peers to advance real-time decisioning. You’ll push state-of-the-art techniques, mentor juniors, and contribute to a data-driven culture across a large retail platform. This is a chance to shape personalised experiences across Nectar and related touchpoints.

Pay / Benefits

• colleague discount
• pensions scheme and life cover
• performance-related bonus up to 20%
• private healthcare
• cycle to work scheme
• season ticket loans

Responsibilities

• Lead on the technical development of algorithms and pipelines aligned to strategic objectives.
• Iterate modelling and optimisation capabilities for continuous learning and real-time decisioning.
• Own sub-projects, mentor junior colleagues, and engage with stakeholders.
• Align to best practices across modelling, experimentation, deployment, and model lifecycle management.
• Coach through doing—share standards by pairing on code.
• Become the technical expert in the team and introduce new approaches.
• Understand business operations, including peak trading periods, to inform modelling.
• Contribute to the wider Data & Analytics community with new techniques and ideas.

Key requirements

• Extensive experience in Data Science with end-to-end problem solving.
• Experience building production systems and measurable value creation.
• Ability to balance commercial needs with technical rigour.
• Experience working in Agile environments and evaluating value vs. technical effort.
• Strong communication of ideas to varied technical audiences.
• Solid grounding in statistical modelling and machine learning, including predictive modelling, causal inference, and experimentation.
• Ability to select appropriate techniques to meet objectives and avoid pitfalls.
• Proficiency in Python and SQL; experience with production codebases, version control, CI/CD, and batch processing.
• Practical experience with cloud-based ML platforms.

• Strong communication across audiences of varying technical background
• Self-motivated and proactive problem-solver
• Collaborative mindset and willingness to coach others
• Statistical modelling and machine learning (predictive modelling, unsupervised learning, causal inference)
• Optimization and decisioning
• Python and SQL programming

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