Role Purpose

The Analyst, Forecasting & Analytics is on the Gorilla Glass Commercial Forecasting Team. You will model major OEM demand at the SKU level and maintain a rigorous record of the assumptions, drivers, and changes behind every forecast. You will be the team's source of truth for why the number is the number - and the person who turns repetitive analytical work into automated, scalable tools that improve the forecast and the broader commercial function.

You will collaborate closely with Account Managers, Product Line Managers, Operations, Supply Chain, and Finance - translating market intelligence and customer signals into defensible forecasts that inform key business decisions.

Key Responsibilities

• Model major OEM demand at the SKU level, building and maintaining detailed by-SKU forecasts for the team's largest customers.
• Own the assumption log. Maintain a rigorous, auditable record of forecast assumptions, drivers, model changes, and revisions - so any number can be traced back to its inputs.
• Maintain detailed SKU-level records for OEMs: shipment patterns, mix shifts, generation transitions, and customer-specific dynamics.
• Use Python (or equivalent) to automate and streamline recurring analytical work across the forecasting team and adjacent commercial functions.
• Apply advanced techniques - statistical modeling, time-series methods, machine-learning where appropriate - to improve forecast accuracy and decision support.
• Analyze historical shipment data, market trends, and customer signals to surface patterns that inform forecasting models.
• Collaborate cross-functionally with Account Managers, PLMs, Operations, Supply Chain, and Finance to validate assumptions and incorporate market intelligence.
• Monitor and evaluate forecast accuracy; identify drivers of misses and implement model adjustments with documented rationale.
• Communicate forecast results, assumptions, and risks to stakeholders clearly to support informed decisions.
• Stay current on modeling techniques, tooling, and industry dynamics; bring useful approaches into the team's workflow.
• Support process improvement that aligns commercial, operational, supply chain, and finance functions on a single forecast.

Experiences/Education - Required

• Bachelor's degree in a quantitative discipline (Mathematics, Engineering, Economics, Statistics, Business Analytics, or related).
• Minimum of 3 years of experience
• Proficiency in Python (or another programming language) for data analysis, automation, and process improvement.
• Strong Excel skills - comfortable with complex models, structured workbooks, and Power Query.
• Experience with forecasting methods, time-series analysis, or predictive analytics.
• Demonstrated rigor in documenting assumptions, drivers, and changes - version-controlled or auditable working files.
• Strong analytical skills - able to interpret complex data, identify patterns, and draw defensible conclusions.
• Strong communication and collaboration skills - able to explain modeling choices to non-technical stakeholders and senior leadership.

Experiences/Education - Desired

• Master's degree
• Proficiency in R