Data Scientist – Fuel Pricing

Role Overview

• Apply statistical and econometric modeling, time series analysis, optimization methods, and generative AI to develop improved approaches to demand modeling, elasticity estimation, price recommendation, competition analytics, and related challenges.
• Develop reusable tools, frameworks, and components to support and accelerate delivery of value from data science.
• Deploy scalable and maintainable solutions to cloud environments, leveraging version control practices and robust code quality and documentation standards.
• Work independently and as part of the Data Science Research team, contributing to research prioritisation and technical direction in collaboration with the Director and Product leadership.
• Demonstrate technical excellence by delivering high-quality, innovative solutions and championing best practices to ensure research outputs are reproducible, scalable, and maintainable.
• Contribute to evaluation and adoption of appropriate tools, programming languages, and technologies.
• Mentor junior team members, sharing knowledge and supporting their professional development.
• Identify and contribute to patent opportunities and the company's intellectual property portfolio.
• Collaborate across Development, Product, Analytics, and Commercial teams to ensure solutions address business challenges and stakeholder objectives.
• Partner with operational teams to ensure data pipelines and infrastructure are robust, secure, and optimized for research and production workloads.
• Communicate technical concepts and outcomes effectively to both technical and non-technical audiences.
• Stay current with developments in data science, machine learning, and AI, applying state-of-the-art techniques to project work.
• Develop comprehensive knowledge of the retail fuel industry to understand domain challenges and help guide product innovation.
• Share knowledge and promote best practices across the team and company.

Requirements

• Ph.D. or master's degree in a quantitative discipline.
• Demonstrated track record of designing, developing, and deploying data science and machine learning solutions in commercial environments.
• Expertise in statistical or econometric modeling and optimization techniques.
• Proven ability to independently manage complex projects under tight deadlines while maintaining high standards of quality and reliability.
• Strong written and verbal communication skills for both technical and non-technical audiences.
• Cross-functional team collaboration experience with product, engineering, and business stakeholders.
• Experience in pricing data science is desirable, particularly within the fuel or retail sectors.

Tech Stack

• Cloud

Benefits

• Flexible working hours
• Professional development opportunities