Kalibrate exists to deliver the right insight, at the right time, to give organizations answers to their most challenging questions.
We’re partners in growth. We serve decision makers across location and fuel pricing in markets all over the world — from high growth emerging concepts to the most established international operators.
Our platforms and analytics solutions directly empower decision-making and provide clear financial value. These decisions help grow economies, create jobs, and improve the communities where we live, work, and play.
Role
Reporting to the Director of Data Science Research, the Data Scientist is a highly skilled individual contributor responsible for designing, developing, and deploying advanced data science solutions across Kalibrate's product portfolio. This role focuses in particular on our pricing product suite, applying leading statistical, machine-learning, and AI techniques to deliver innovative solutions for fuel pricing while contributing to the technical excellence of the Data Science Research team.
Key responsibilities include:
Data Science Solution Development & Delivery
- 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.
Technical Excellence & Mentorship
- 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.
Collaboration & Communication
- 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.
Innovation & Continuous Learning
- 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.
Qualifications & Profile
- 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.
Technical Skills & Experience
- Advanced proficiency in Python and/or R for data science development.
- Proficiency in SQL for data extraction, transformation, and analysis.
- Experience with version control (Git) and modern software engineering practices including code review and collaborative development.
- Familiarity with using generative AI tools such as Github Copilot to support development and enhance productivity.
- Knowledge of solution deployment with cloud platforms (preferably Azure), including containerization (Docker) and CI/CD pipelines is desirable.
Location & Travel
This a remote role within the UK. Travel to our offices in Manchester city centre, or client and partner locations, may be required for meetings and events.
The Data Science Research team operates across multiple time zones globally, so working hours may occasionally need to flex to accommodate necessary collaboration with international colleagues.
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