Lead the infrastructure data science team. We leverage vast amounts of internal data-- capacity utilization, infrastructure cost, product app logs, etc.-- to optimize Salesforce's global infrastructure.

- Built and developed a high-performing data science team of 6+ that supports capacity planning, performance engineering, and finance teams with advanced infrastructure analytics and internal forecasting tools. - Managed the development of an internal changepoint and forecasting libraries based on Facebook Prophet. Currently supports 20k+ system metric forecasts each month and 200k+ customer workload forecasts for capacity planning use cases. - Created an internal infrastructure data catalog in partnership with the Salesforce data governance team. Over 100+ documented tables and 5 knowledge articles covering key infrastructure usage, customer workload, and cost data sets. Internal data catalog supports 70+ internal users and 2k+ monthly queries.- Led team-wide data management maturity efforts. Through a corporate-wide evaluation, our team increased data management score +36% by intentional improvements to our data management practices. - Enabled Tableau on infrastructure data stores; 600+ internal MAU, 158+ datasources, and 170+ workbooks used throughout Salesforce to produce actionable insights by leveraging governed infrastructure data.

Developed in-depth data analyses with app log, system utilization, and financial data to inform infrastructure expansion strategy as an individual contributor.

Performed strategic and financial due diligence on potential early stage investmentsacross a wide array of enterprise IT and data platform startups Worked closely with portfolio companies to develop initial and evolving businessmodels, financial forecasts, operational plans, and strategic pivots

Built valuation frameworks and financial models to support potential acquisitions in the enterprise cloud space to fuel Azure's growth. Performed technical due diligence and provided analyses for 6 closed deals representing $XXXM in deal flow.

Evaluated the relationship between revenue, costs, cloud infrastructure utilization,and margin structure within the Microsoft Azure compute and storage businesses.

Formulated and implemented mixed-integer programming algorithms in C++/CPLEX to improve small satellite communication operations with research funding through NSFPublication: “Optimization-based scheduling for the single-satellite, multi-ground station communication problem”. Computers & Operations Research, 57, 1-16

Implemented mathematical programming models in C++/CPLEX, performed computational experiments, and presented results.