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Worky in the United Kingdom seeks a Full Stack Engineer with a data science focus to bridge data engineering and user-facing dashboards for Zula 2.0, the platform ranking and fusing rail inspection data. This seat decides what analysts and customers see and drives progress through year-end.
You will design data pipelines, build dashboards with React, develop RESTful APIs, and deploy ML models on AWS, collaborating with analysts, engineers, and product managers across the rail business.
We are looking for a Full Stack Engineer with a data science focus who also brings frontend experience with React. You will bridge the gap between data engineering and user-facing applications on Zula 2.0, the platform that ranks and fuses the output of our rail inspection systems – building both the backend data services and the interactive dashboards and tools that make inspection data accessible to stakeholders across the rail business. This is the seat that decides what our analysts and customers actually see. Zula 2.0 is the critical path for the team through the end of the year.
We expect an exceptional level of drive and ambition. You think beyond today's work to what the team and organization need next, champion bold ideas, and see them through. Your hunger is infectious – it inspires those around you to aim higher. You should be someone who puts the team first. You share credit openly, admit when you are wrong, and welcome feedback as an opportunity to grow. You are comfortable saying "I don't know" and asking for help when needed. Strong interpersonal skills are important for this role. You should have good instincts for working with different people, listen actively, navigate disagreements constructively, and communicate clearly with both technical and non-technical audiences. You should be able to quickly grasp complex problems that span multiple systems or domains. We expect you to design effective solutions for non-trivial requirements, identify root causes efficiently, and consider performance, scalability, and maintainability in your approach.