Oct 2024 – Jan 2026 · 1 yr 3 mos

• Forecasted data center space and power needs for racks, network, cooling and designed comprehensive scenario planning framework that enabled executives to optimize data center investments through strategic energy contract negotiations and sprung structure deployment decisions.
• Architected 2-year rack touch workforce planning model– stitching growth, migration, and retrofit data, identifying manpower bottlenecks and enabling optimized proactive resource allocation across global operations.
• Infrastructure optimization initiative resulting in $1B+ operational savings through data driven gen AI rack redeployment strategy
• Developed comprehensive power stranding risk models for tent and cable data centers, identifying 5-68MW potential stranding per region and creating mitigation strategies to prevent stranded capacity costs.

Jan 2022 – Nov 2023 · 1 yr 10 mos · San Francisco Bay Area

• Owned demand and supply planning for compute, space and power of 330+ global data centers.
• Led automation of compute planning reducing runtime from days to minutes and enabling scenario planning.
• Enhanced forecasting accuracy through ML implementation of signals like sales pipeline, churn signals, macroeconomic factors etc.
• Managed infrastructure budget planning and optimization

Aug 2019 – Oct 2021 · 2 yrs 2 mos · San Francisco Bay Area · On-site

• Owned delivery performance KPIs of Maxim's Supply Chain
• Reduced inventory costs $24M through simulation modeling
• Improved delivery prediction accuracy 10% using DoE
• Achieved $1M transit cost savings through route optimization
• Enhanced on-time delivery from 60% to 80% using ML model

Aug 2018 – Dec 2018 · 4 mos · San Francisco · On-site

• Reduced the turnaround time of cancer genomic test to guide treatment therapies(UCSF500) from 23 to 14 days.
• Created and compared the optimistic and average case Gantt chart to identify the potential areas for improvements.
 Studied the distribution of all processes' time to shorten the tails by addressing the uncertainties in the respective operations. Minimized the mean time by suggesting parallel processes and automations.

Aug 2017 – May 2019 · 1 yr 9 mos · San Francisco Bay Area · On-site

• Logistic Network Design & Supply Chain Management (INDENG 153), Prof Susan Cholette
• Optimization Analytics (INDENG 240), Prof Ilan Adler
• Risk Modeling, Simulations and Data Analysis (INDENG 241), Prof Xin Guo
• Computational Models of Cognition (Cog Sci 131), Prof Steve Piantadosi
• Lectured and arbitrated discussion sections, held office hours to assist 300+ students in the course, developed evaluation guidelines, facilitated case studies and reviewed projects.

Nov 2016 – Jul 2017 · 8 mos · Palo Alto · On-site

• Taught the fundamental coding skills and algorithms to students one-on-one.
• Programming language used: Python, Scratch.

Jun 2015 – Nov 2015 · 5 mos · Volvo Eicher Power Train (VEPT) plant, India · On-site

• Developed Management Information System(MIS) dashboard that drove business decisions across different lines of business and teams within operations.
• Optimized the resource allocation of the plant which was in the Expansion Phase-2 from 50,000 units per annum to 75,000 units per annum by reducing the machine to man ratio by 16% and the floor space utilization by 44%.

May 2014 – Aug 2014 · 3 mos · Indore Area, India

• Performed As-Is Analysis and carried out the Process Mapping of the production line.
• Reduced the Mahindra E-06 engine's component rejection by 20% by applying Root Cause Analysis to identify the source of leakage in the cylinder head of the engine. Implemented and standardized the corrective measures.