Commercial & Data

Role Overview

As a Data Science Graduate, you will join a cohort of early-career professionals and work hands-on with experienced data scientists to turn raw information into actionable business insights. Day to day, you will handle everything from scrubbing messy datasets to building prototype models and presenting your findings to stakeholders, directly supporting data-led decision-making across the company. This role is designed to bridge academic theory with commercial practice, giving you exposure to the full project lifecycle in a supportive, learning-focused environment.

Key Responsibilities

• Cleanse, transform, and validate large, multi-source datasets to ensure accuracy and readiness for analysis.
• Support senior team members in constructing and testing statistical models, predictive algorithms, and machine learning prototypes.
• Build and maintain interactive dashboards and scheduled reports using modern data visualisation tools to surface key business metrics.
• Write clear documentation for data pipelines, model logic, and analytical code to promote reproducibility and knowledge sharing.
• Actively contribute during team discussions, proposing data-driven approaches to solve specific operational or strategic challenges.
• Assist with ad hoc data requests from different departments, translating business questions into analytical tasks.
• Participate in code reviews and peer feedback sessions to improve technical quality and collaborative skills.

Requirements & Qualifications

• Currently enrolled in, or have graduated within the past 12 months from, a Master’s or Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or another quantitative discipline.
• Solid grasp of core statistical concepts and data modelling techniques, with the ability to apply them practically.
• Proven proficiency in SQL for extracting, joining, and manipulating data from relational databases.
• Hands-on experience with at least one data visualisation platform such as Tableau, Power BI, or Looker.
• Strong problem-solving mindset, able to break down ambiguous questions into structured analytical steps.
• Exceptional attention to detail when handling data, validating outputs, and reviewing code.
• Demonstrated ability to articulate complex analytical findings in a clear, non-technical manner to diverse audiences.