Data Solutions Analyst / Scientist

About the role

We are looking for a Data Solutions Analyst / Scientist to lead forecasting, AI‑driven models and scalable data products that support national network operations. The role sits in the Network Insights, Analytics and Reporting team and works closely with Operations, Planning, Finance, Commercial and Technology stakeholders.

Key responsibilities

• Lead end‑to‑end network forecasting across first, middle and last mile, enhancing short‑ and long‑range volume forecasts.
• Build scenario models, sensitivity analyses and integrate internal data with external economic, demographic and market drivers.
• Design and maintain production‑grade data models and forecasting pipelines using SQL, GCP and BigQuery, applying analytics engineering practices such as testing, CI/CD and version control.
• Apply statistical, machine‑learning and AI methods (time‑series, regression, causal modelling, anomaly detection, classification, clustering) to continuously improve forecast accuracy.
• Partner with operations, planning and commercial teams to translate complex outputs into clear, decision‑ready insights and influence trade‑offs between cost, service, capacity and performance.

Required profile

• 5+ years of experience in forecasting, data science or advanced analytics, preferably in logistics, supply chain or operations.
• Strong experience building forecasting models using time‑series, regression or machine‑learning techniques.
• Proven ability to work with large, complex, multi‑source datasets and to engage stakeholders effectively.

Required skills

• Advanced SQL and experience with cloud platforms (e.g., GCP, BigQuery).
• Python or R, and forecasting tools such as Prophet, ARIMA, XGBoost.
• Analytics engineering practices: Git, CI/CD workflows, testing.
• Data visualisation and storytelling tools (Tableau, Looker).