We are a pan-European logistics company with operations in eleven countries and a data team that has, until recently, focused primarily on operational reporting. That focus served us well. It no longer captures everything we need. The business now expects our data function to support decision-making with forward-looking analysis — demand forecasting for route planning, anomaly detection on shipment delays, capacity optimisation modelling — in addition to the operational dashboards we continue to maintain. We are seeking a mid-level analyst who sits at the intersection of classical business intelligence and applied AI techniques. You will have strong SQL and BI skills. You will also have enough Python fluency and statistical grounding to build exploratory predictive models, evaluate their assumptions critically, and communicate both the findings and the limitations clearly to a non-technical leadership audience. Precision and intellectual honesty are non-negotiable in this role. We would rather an analyst who tells us a model is unreliable than one who presents an overfit result with confidence.
Responsibilities
Own and maintain logistics performance dashboards used by regional directors and the COO
Build demand forecasting and capacity models to support route planning decisions
Conduct ad-hoc analysis for senior leadership with written conclusions and documented limitations
Collaborate with the engineering team on data quality improvements upstream of your models
Present analytical findings in monthly leadership reviews
Requirements
4+ years in business intelligence, data analytics, or a closely adjacent analytical role