NAINA CHAUHAN

Advised a leading cement manufacturer on AI-led transformation across 57 manufacturing use cases, converting ambiguous needs into a prioritized workstream. Evaluated use cases end-to-end using data analysis, stakeholder interviews, and process research to deliver structured recommendations and measurable KPIs. Built a fact-based model integrating multi-level plant data to quantify power savings and cashflow impact, presenting decision-ready deliverables for senior stakeholders. Aligned priorities with cross-functional client teams across seniority levels, supporting adoption of recommended solutions.

Drove go-to-market strategy for a Generative Engine Optimization (GEO) offering in a largely autonomous, fast-moving environment. Conducted market and competitor research and engaged in direct client outreach to validate demand. Shaped GTM strategy through actionable recommendations based on customer and competitor insights.

Enabled timely disposition of ~1,200 lots (~32% of site volume) over 30 months through fact-based yield analysis, sustaining fab throughput. Improved site yield to 97.2% via process optimizations and resolved 30%+ of site issues through structured root-cause analysis on high-priority lots. Identified a tool-induced yield issue across 100+ production batches, mitigating quality risk of $3.75M+. Led capital initiatives recognized with the Epsilon Global Execution Award for $39M+ in cost savings. Partnered with global stakeholders at US Fab9 to align operations and decisions, improving test-time efficiency by 25%+ across three technology nodes.