A hybrid role at Extreme Networks.
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We are seeking a “Supply Chain AI & Automation Analyst” to join our Extreme Networks Global Operations organization, where you'll turn complex operational data into clear, actionable insight that drives decisions and automation across our Global Supply Chan and Order Management teams. This role sits at the intersection of analytics, AI, and supply chain strategy, partnering with cross-functional teams to identify opportunities, build analytical products, and tell the stories behind the numbers. The ideal candidate is a curious, technically strong analyst who is equally comfortable writing SQL, using AI tools, framing a business problem, managing a project, and presenting findings to stakeholders. You should be excited about the rapid evolution of AI and agentic workflows and how they can be applied to supply chain decision-making and you should be actively using AI tools in your work today.
A note on experience
This role requires commercially delivered analytical work. We will ask you at interview to walk through a specific project from problem through to business outcome that you owned and delivered in a professional setting. Academic or course-based projects do not qualify. If your experience is primarily from an academic programme, this role is not the right fit at this time
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.
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).
Programming for analytics: Python or R for modelling, automation, and analytics workflows.
BI and visualization tools: Tableau, Sigma, Power BI, Looker, or similar — both for building and for design literacy.
ERP / source systems: Exposure to Oracle Fusion Cloud or similar transactional systems.
Practical experience applying agentic workflows (e.g., LLM-based assistants, retrieval-augmented analytics, automated reasoning agents) to analytical or operational problems.
Master's or PhD in a quantitative field (Statistics, Operations Research, Engineering, Physics, Economics, Data Science, Supply Chain, Mathematics, or related).
Forecasting and optimization: time-series methods as well as other optimization techniques.
Machine learning fundamentals: classification, regression, clustering, and an understanding of when ML is and isn't the right tool.
Process improvement methodologies: Lean, Six Sigma, or equivalent structured problem-solving frameworks.
Stakeholder management and influencing: navigating ambiguity, managing competing priorities, and building trust with non-technical partners.
Within 3 months: deeply understand our supply chain data landscape, key stakeholders, and top-priority business questions.
Within 6 months: deliver at least one high-impact analytical product or AI-enabled workflow that changes how a decision is made.
Within 12 months: become a trusted analytics partner to supply chain stakeholders and a contributor to the broader analytics team's standards and practices.…
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Extreme Networks, Inc. is an American networking company based in Morrisville, North Carolina. Extreme Networks designs, develops, and manufactures wired and wireless network infrastructure equipment and develops the software for network management, policy, analytics, security and access controls.
Source: Wikipedia
