Senior Data Scientist

Opportunity Overview
We are seeking a Senior Data Scientist with a strong background in Applied Mathematics to lead our modelling and simulation efforts. In this role, you will not just be developing algorithms; you will be the architectural lead in simulating how our robotic solutions interact with customer environments.

Your work will be pivotal in the logistics industry, using data-driven insights to predict performance, optimise throughput, and provide our clients with the certainty they need to deploy groundbreaking automation.

Who You Are
You are a seasoned practitioner who thrives on applying mathematical rigour to solve messy, real-world problems. You understand that a model is only as good as its ability to inform a business decision. With several years of experience under your belt, you are comfortable navigating the ambiguity of customer requirements and turning them into robust, high-fidelity simulations. You are a collaborator who can speak the language of both software engineers and commercial stakeholders.

Your Impact
• Customer Modelling: Lead the development of bespoke models that simulate client environments, ensuring our robotic systems are perfectly tailored to their operational needs.
• System Simulation: Design and execute complex simulations to stress-test system throughput, bottlenecking, and ROI before any hardware is deployed.
• Strategic Integration: Work closely with software engineers and product teams to integrate analytical models into our core product offerings.
• Technical Mentorship: Act as a subject matter expert within the business, guiding junior team members and maintaining high standards for code quality and mathematical validity.
• Advanced Analytics: Use cutting-edge statistical methods to extract actionable insights from large datasets generated by our global fleet of autonomous machines.

Who We’re Looking For
• Experience: Significant professional experience (typically 5+ years) in Data Science, Applied Mathematics, or a simulation-heavy Engineering role.
• Education: An advanced degree (MSc or PhD) in Mathematics, Physics, Computer Science, or a related quantitative field.
• Modelling Expertise: Proven track record in building operational simulations and predictive models that have been used in a commercial or industrial context. • Technical Stack: Expert-level proficiency in Python (specifically libraries like NumPy, Pandas, and SimPy) and a strong working knowledge of C++.
• Soft Skills: The ability to communicate complex technical findings to non-technical customers and internal leadership.
• Tooling: Familiarity with modern data visualisation tools and version control (Git) in a collaborative environment.