Alex Gilgur, Phd Email & Phone Number

Developing the capability for capacity planning and management for a low-earth orbit (LEO) satellite constellation delivering connectivity to unserved and underserved parts of the world. Forecasting, capacity planning, statistical process control (SPC). Implementing SixSigma methodology for network capacity management. Automation of root cause analysis (RCA) and bottleneck detection. Defining the requirements and overseeing implementation of components for capacity management and planning.As founding member of the organization-wide Science and Sumulation (Sci/Sim) team, I authored the proposal, Business Requirement Documents (BRDs), and other documentation to help the executives in forming the team with an organization-wide scope to provide “Science as a Service”, including Data and Applied Science, Data Engineering, and Simulation. Formulated the list of critical-path use cases that such a team would address. Developing proof of concept (PoC) solutions for these use cases. Working with the managers, upper management, and organization executives to reach alignment on first-year goals and roadmap for the Sci/Sim team.

As TL and SME: Created and led XFN teams developing and implementing capacity planning and management systems. Mentored new members of the team. Helped team members identify interesting impactful projects. Proposed, developed, and implemented a novel queueing-based ML predictor platform for estimation of capacity needed to support a given transitive demand on any service. Developed a system for predicting downstream services’ demand based on frontend traffic. Developed and implemented a system accurately predicting transitive power consumption based on direct measurement of CPU cost. Organized team members, partners, and customers in support of the proposed systems.

Worked as data scientist in a XFN team developing a distributed-tracing system for measuring Infrastructure cost of user requests (known as Canopy outside FB). Developed and implemented innovative techniques to extract unbiased cost from raw measurements. Developed and implemented a novel explanatory power model based on Universal Scalability Law (#USL). Created and productionized an innovative Monte-Carlo system for estimating statistical power of arbitrarily distributed data. Mentored other team members. Taught a class on Applied ML. Co-developed and presented a tutorial session on ML at the #CMGImpact 2019 International Conference.

Was the first Data Scientist on the Network Planning team. Created network demand forecasting capability from the ground up. Helped build the Network Data Science team to 6 contributors, mentored new members of the team. Developed and implemented novel methods for forecasting heterogeneous network demand. Created a novel metric of compressibility for manifolded traffic. Developed a queuing-based comprehensive causal model of network and compute demand for capacity management and planning for highly heterogeneous systems. Its subsystems became the default solution for network capacity planning. Worked with network and software engineering teams. Evaluated data quality and developed novel techniques for data pretreatment and building robust predictive models. Published two papers at #CMGImpact.

Mountain View, Ca, Us

San Jose, Ca, Us

Key contributor to, leader in, and initiator of, a number of Site Operations, Capacity, and Performance projects, providing technical expertise to support efforts to make PayPal the best online payment destination.Point of Contact for questions on operation, performance, and sizing of the site infrastructure.Projects:SPC: Leading a team of experts implementing an enterprise-level Statistical Process Control system. A number of technical challenges have been innovatively and successfully resolved using advanced statistical techniques and in-depth knowledge of site operation. Lean Operations: Project Lead on a number of technical projects for continuous optimization of resource usage.Business Forecasting: Developed and implemented an analytical tool for forecasting business metrics using a combination of time-series analysis and regression modeling.Business Analytics: Created a Know-How Consumer Confidence Index as a proprietary predictor of customer behavior and business dynamics. Implemented a suite of tools for computing settings required to support a given business metric value (payment rate) while guaranteeing a better than 99.9% site availability. This approach allowed us to improve utilization of existing capacity by 30%. Designed, supervised execution, and analyzed results, of a series of experiments to identify the optimal operation zone of an eight-core load balancer (f5) . Transitioned the results into production. Saved 15% capacity while maintaining the same 99.9% site availability.Change Detection: Implemented a suite of tools detecting long-term changes and short-term process pathologies in key performance metrics.Other:Preparing and presenting technical and non-technical slide decks and white papers for peers and for executives.Participating as a mentor in PayPal Technology Mentorship Program.Developing tools for data mining and analysis.(For more details, please see the resume)

Lead analyst and lead software developer for the Analytics Group, which evaluates, develops and, if necessary, invents analysis and forecasting techniques and tools to meet Enterprise performance monitoring and capacity planning needs.I incorporated sophisticated univariate and multivariate analysis techniques to address problems involved in data analysis, forecasting and capacity planning. This enables IT organizations to proactively match the supply of hardware infrastructure resources with the projected demand for data storage, and by doing so, successfully avoid expensive outages, and save both OpEx and CapEx. Several techniques are innovative, and I am an inventor on patents issued in the fields of capacity planning, data pattern analysis, model quality evaluation and automated bulk analysis and forecasting. Developing a Road Map and a Cost-Benefit analysis for further development of the Business Unit's analytical capabilities, aimed at widening the portfolio of solutions being offered to the customer.I am also providing instruction, presentations, and internal expertise in applied math and data analysis to the sales force, support engineers, management, executives, and customers. Clearly communicating highly technical results and methods in an accessible and useful way.

(MonoSphere became part of Quest in December 2008)

Led Company’s effort in conducting a NASA study of human performance under stress, using Air Traffic Control (ATC) operations as model environment. Results made it possible for the FAA to improve airport throughput and aviation safety.

Provided technical leadership and management during installation, ramp-up, and initial operations of a semiconductor fab startup. The fab now produces digital X-Ray detectors used in GE radiology equipment all over the world.

Was in charge of production operations and environmental compliance at an etching facility, developing production and waste treatment processes and establishing SPC for the production floor.Built from the ground up a state-of-the-art chemical laboratory in an etching facility.

Prepared proposals, executed projects, and implemented modern technology for the environmental protection.

Designed and implemented chemical process control systems. Developed and implemented in-line analytical instrumentation for a variety of process liquids and gases.

Phd Candidate, Systems Engineering

Applied Mathematics And Operations Research

Ms, Control Systems And Instrumentation