Data Scientist

Role Overview

The Data Scientist joins the Data Science & Analytics function and reports directly to the Data Manager. This position turns complex, varied datasets into practical direction for the organisation: it investigates what data can reveal about mission-critical questions, then designs statistical, econometric, and machine-learning solutions that sharpen planning and operational choices. The role is central to building scientific and technical depth across Data, Analytics & AI while ensuring every insight is accurate, timely, and aligned to business priorities.

Key Responsibilities

• Develop econometric, statistical, and machine-learning models for forecasting, classification, clustering, pattern detection, sampling, and simulation.
• Strengthen the Data, Analytics & AI department’s scientific toolkit and technical standards so current and future data initiatives can scale.
• Produce forward-looking recommendations by learning the problem space and mapping available data assets, particularly for strategic programmes and value-focused efforts.
• Run exploratory and ad-hoc analyses on large datasets tied to business strategies, using data mining and statistical testing to surface meaningful signals.
• Convert findings into actionable insight through predictive modelling, segmentation, customer profiling, survey design, and related advanced techniques.
• Work alongside other data scientists to document challenges, share results, and present clear recommendations to stakeholders so decisions improve and performance rises.
• Support project delivery by clarifying scope, meeting service specifications, and completing work on schedule.
• Help the team continually improve its ways of working, and maintain compliance with policies, procedures, statutory rules, audit deadlines, competency assessments, and stakeholder expectations.

Requirements & Qualifications

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Machine Learning, Economics, or another quantitative discipline; equivalent working experience may be accepted.
• Big Data, Data Science, or Generative AI certification from a recognised institution.
• Minimum three years’ experience in business analysis, informatics, or business outcomes research within a fast-paced, complex organisation.
• Hands-on experience deploying generative AI and agentic AI use cases is an added advantage.
• Practical grounding in probability, statistics, time-series analysis, or econometrics.
• Familiarity with machine learning methods such as linear regression and decision trees.
• Strong Python skills, plus experience with a cloud data science platform such as AWS SageMaker and solid knowledge of big data platforms.
• Creative, self-directed mindset with the drive to work independently.
• Strategic thinking and the ability to analyse complex problems, form action plans, and deliver results.
• Ability to combine and interpret varied data and information, then recommend strategies.
• Strong stakeholder communication and relationship-building skills, with a focus on customer satisfaction and expectation management.