Partner with supply chain stakeholders to scope problems and translate them into structured, measurable, automated workstreams.
Build and maintain python/SQL/Snowflake-based data models, dashboards, and self-service analytics for our global operations teams
Help operationalize AI and agent-based solutions to automate recurring analyses, augment decision support, and supply chain processes.
Apply statistical methods to inform data driven decisions across our global operations function.
Manage your projects end-to-end: scoping, stakeholder alignment, data discovery, modelling, validation, and rollout.
Translate analytical findings into compelling narratives (written, visual, and verbal) tailored to operational, business, and technical audiences.
Define and track KPIs that measure supply chain performance and flag interventions when metrics drift.
Contribute to ongoing improvements in data quality, documentation, and analytical standards across the team.
Requirements
3-5 years experience in business analytics, data analytics, or a comparable quantitative role.
Demonstrated use of AI tools such as Claude, MS Copilot, or ChatGPT – in an analytical workflow, with a genuine appetite to develop agentic and automation capabilities in role.
Strong python skills and hands-on experience with Snowflake (or a comparable cloud data warehouse such as BigQuery, Redshift, or Databricks).
Demonstrated project management ability, owning deliverables across multiple stakeholders and timelines.
Solid grounding in descriptive statistics, and analytics fundamentals.
Strong data storytelling skills: the ability to distil complexity into clear visuals and narratives that drive action.
Supply chain domain knowledge: familiarity with demand and supply planning, inventory optimization, order management, logistics, procurement, or manufacturing operations.
Bachelor's degree in a quantitative field (e.g., Statistics, Operations Research, Engineering, Physics, Economics, Data Science, Supply Chain, Mathematics, or related).