Gaurav

Enabled investment decisions for a $2.2B private equity deal (client with $7B+ AUM) by identifying key risks via detailed financial and operational due diligence, optimizing value creation and returns.

Supported global expansion for a $200B global media conglomerate by conducting strategic and commercial due diligence for new product entry into Southeast Asia, aligning recommendations with regional consumer behavior.

Delivered M&A strategy for a ~$90B semiconductor client by leveraging data insights from an 8.3% CAGR sector to assess long-term strategic viability and investment impact.

Improved product-market fit for a $200M+ wipe manufacturing company by identifying Key Purchase Criteria (KPCs), enabling product adjustments and forecasting ~8% growth over 5-6 years.

Conducted commercial due diligence for a private equity firm evaluating a $35B+ pharmaceutical packaging company, analyzing market dynamics, KPCs, and growth drivers.

Devised go-to-market strategy for an EHR software firm in a ~$12B US market (45% of global EHR revenues) by conducting market analysis of top U.S. hospitals and identifying key competitive positioning indicators.

Executed strategic due diligence for an email security software firm, assessing ~$2.1B in 2024 with ~60% cloud deployment share by analyzing customer sentiment and competitive positioning.

Developed a browser extension for web data scraping, reducing manual effort by ~40% and saving time through streamlined data extraction and processing for multiple teams.

Reduced manual effort by ~20% through maintaining daily logs and device data in structured MS Excel sheets, thereby streamlining operational tracking.

Improved equipment reliability and minimized downtime by supporting the Maintenance and Inspection team in asset monitoring.

Enhanced documentation quality and internal communication by contributing to daily maintenance reporting and technical documentation across teams.

Supported preventive maintenance planning through analysis of historical logs and recurring equipment issues, enabling data-driven prioritization of high-risk components.