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Summary

I bring a unique combination of depth of technical knowledge along with an extensive experience across industries and business functions in AI, optimization and machine learning. Along with my depth of knowledge and experience, my business school background enables me to grasp the nuances of a business decision quickly and translate that to technical model and algorithm requirements. Also, I am adept at breaking complex business requirements, and am able to go from business concepts to final implementations. 

My current work in building LSNLOPT, an extensible framework for large scale optimization in C++20 and graph theoretic algorithms shows my expertise in building complex scalable algorithms. I was a hands-on Manager of Decisions Sciences at Kohl’s; there, I used Python and tools like GAMS, GUROBI and large-scale data processing tools to build models for assortment planning and improving supply chain across 1100 stores nationwide. Additionally, I build prototypes to understand feasibility and get business approvals – for example at Kohl’s our first assortment planning prototype was intractable. I am focused on advancing optimization and machine learning, as demonstrated both in my current work on stable large scale optimization algorithms, and earlier in developing probabilistic clustering algorithms.

Skills

  •  Modeling: Machine Learning | Statistical Modeling | Math Programming | Discrete Event Simulation
  • Algorithmic: Online Algorithms | Graph Algorithms | Vehicle Routing | Large Scale Nonlinear Optimization Algorithms
  • Technologies: Python, C++, R, SAS, Java, FORTRAN | GUROBI, CPLEX, COIN-OR | GAMS, AMPL, SIGMA, SLAM | Oracle PL/SQL, Microsoft Transact SQL, Teradata SQL, HDFS – Hive QL.

Work experience

Director - Machine Learning and Optimization

December 2020Present
GS Ravindra, PhD Consultants, Palo Alto, CA
  • Collaborated with faculty from UT Austin and Rutgers, integrating cutting-edge research.
  •  Building LSNLOPT, an extensible and efficient C++20 framework for large scale super-sparse constrained nonlinear optimization - to shrink algorithm researcher’s effort by 75%.
  • Developing innovative randomized algorithms to address graph theoretic problems like fill-in reduction.
  • Improving the optimization robustness by addressing ill-conditioning in the models.
  • Developed probabilistic clustering algorithm that was implemented in python and tested over large multi-dimensional data sets from cancer therapy – taking 80% less computational effort than comparable EM methods.

Manager - Decision Sciences

June 2022May 2023
Kohl’s Corporation, Palo Alto, CA
  • Led the Decision Sciences team in building models and algorithms for merchandizing, marketing, supply chain and logistics.
  • Built a framework for assortment planning - purchase order planning and space optimization for 1100 stores nationwide and six fulfillment centers to improve gross margins.
  • Designed inventory allocation mechanism to stores and fulfillment centers based on near term sales forecast, to reduce markdowns and unmet demand costs. 

Senior Principal Data Scientist, Lead - Machine Learning and AI

October 2018November 2020
Oracle Corporation, Redwood Shores, CA
  • Led the application of AI/ML techniques for User Experience Research, building tools for UX Designers of IaaS, PaaS, and SaaS products.
  • Designed and developed Python tools utilizing libraries such as nltk, spacy, and scikit-learn, which helped conversational UX designers, achieving a "first turn" accuracy of 90% for chatbots of enterprise applications.
  • Executed cloud infrastructure user segmentation and conversion modeling with scikit-learn, successfully identifying the 5.3% of users who upgraded from free trials, aiding in targeted marketing strategies.
  • Reduced time taken by 65% for a 7-member team analyzing click history data of enterprise customers by standardizing path analysis in R and Python.

Principal Data Scientist – Machine Learning and AI

June 2017October 2018
First Tech Credit Union, Mountain View, CA
  • Led the development and deployment of advanced AI/ML models for marketing, risk, and collection function.
  • Implemented a next best offer model in R using random forests and neural networks, achieving a 21% increase in additional product uptake.
  • Rolled out a delinquency prediction model in R, utilizing random forests and logit, which optimized the 30-member collection team's effort.
  • Modeled probability of default, exposure at default, loss given default in R for a $5B portfolio of mortgages – to assist Chief Risk Officer in computing expected credit loss.

Senior Manager - BI and Data Sciences

February 2014February 2017
Symantec Corporation, Mountain View, CA
  • Drove the integration of AI/ML approaches into service strategy, workforce management, and capacity planning, enhancing the efficiency of technical services group.
  • Developed a comprehensive two-year roadmap for a $500M federated customer support operation, targeting a 10% reduction in annual support costs.
  • Recommended innovative solutions such as case volume forecasting, agent scheduling, and customer segmentation to optimize support operations.
  • Engineered a queueing model to standardize processes and simplify agent and case states, achieving potential annual savings of 5-10% by addressing factors like long service durations, priority interrupts etc. overlooked by existing vendor models for support operations.
  • Conducted a critical analysis of a board decision to eliminate a premium enterprise service based on gross margins alone. These customers constituted 93% of enterprise segments, had a 12x higher cross sell and 18% higher renewal rates prompting a reversal of the decision.

Director - Data Sciences

November 2012February 2014
Vidya Insights Ltd., Bangalore, India
  • Led the design of predictive and prescriptive components for an AI/ML startup, focusing on Texas energy retailers such as TXUE and Reliant.
  • Developed meter-level demand forecasting models, aggregating data to forecast demand at the local market level, effectively reducing spot purchases.
  • Designed peak demand response strategies at the consumer level during adverse weather conditions, that would result in reduced spot purchases by the energy retailer.
  • Engineered proactive customer alert systems, enhancing customer engagement.

Associate Vice President, Practice Leader - Global Advanced Analytics Practice

August 2008October 2012
HCL Technologies, Bangalore, India
  • Invited by the CEO to drive innovation in technology services, successfully reaching Fortune 100 customers with business-focused solutions.
  • Establishment an advanced analytics practice from the ground up, securing financial services and other US clients, resulting in $6M direct annual revenue and a 59% gross margin, with average margin per person 4.5 times the company- wide average.
  • Built and led a 24-member team, focusing on customer acquisition, cross-selling, segmentation and profiling, market-mix, and text analytics, driving significant business growth and innovation.
  • Program managed a 15-member cross-disciplinary team of practice heads to launch a new business process-centric infrastructure management service, including a customer-paid proof of concept for JP Morgan & Chase.
  • Developed and implemented innovative components like ProcessWatch and PathFinder process libraries, contributing to the service influencing over $600M in large deals within its first year.
  • Focused on strategic areas relevant to business growth, positioning HCL Technologies as a leader in advanced analytics and technology services.

Tenured Associate Professor - Production and Quantitative Methods

August 2004August 2009
Indian Institute of Management, Ahmedabad, India
  • Delivered advanced courses in Mathematical Programming and Statistics to MBA students, and Nonlinear Optimization to PhD students.
  • Conducted pioneering research on complex graph theoretic problems like the Traveling Salesman Problem and Facility Location.
  • Explored optimal power flow solutions for real-time load dispatching in utility grids, leading to enhanced energy management and operational efficiency.
  • Provided expert consultation on quantitative methods, offering strategic insights and solutions to complex problems faced by organizations.

Education

Ph.D. Management Science and Information Systems

University of Texas at Austin - The Red McCombs School of Business, Austin, Texas
  • Research: Large scale discrete and nonlinear constrained optimization.
  • Minors: Distributed Computing, Computational Theory

MBA - Finance and Information Systems

Xavier’s School of Management (XLRI), Jamshedpur, India

BS - Chemical Engineering

Indian Institute of Technology, Varanasi, India

Publications

  • A Fast Tabu Search Implementation for Large Asymmetric Traveling Salesman - OPSEARCH, Springer (2012).
  • Implementing Tabu Search to Exploit Sparsity in ATSP instances. W.P. No. 2008-10-02, Indian Institute of Management, Ahmedabad (2008).
  • HCL Technologies: Employee First, Customer Second - Case Study UVA-OM-1366, Darden Business Publishing, University of Virginia (2008).
  • Scaling Sparse Constrained Nonlinear Problems for Iterative Solvers - W.P. No. 2006-08-06, Indian Institute of Management, Ahmedabad (2006).
  • Scaling Sparse Matrices for Optimization Algorithms - W.P. No. 2006-08-05, Indian Institute of Management, Ahmedabad (2006).
  • Computational experience with a safeguarded barrier algorithm for sparse nonlinear programming - Computational Optimization and Applications, vol 19, pgs 107-120, Kluwer Academic Publishers (2001).
  • A single server queue with cyclically indexed arrivals and service times - Queuing Systems: Theory and Applications, vol 15, pgs165-198, JC Baltzer AG, Science Publishers.
  • INTOPT: an interior point algorithm for large scale nonlinear optimization - Doctoral Dissertation, The University of Texas at Austin.
  • A textbook for managers on using quantitative methods - Mathematical Programming for Managers - TBD.

Patents

  • Detecting wasteful data collection - US 8,825,609 · Issued Sep, (2014).
  • Resource management using environments - US 8,635,624 · Issued Jan, (2014)

About me

  • Personal Interests:
    • Travel, Reading, Hiking, and supporting a Delhi non-profit Niramaya in addressing preventable blindness
  • Fun Facts:
    • I go by initials GS. 
    • I have been serial entrepreneur – once in Austin, TX and twice in Silicon Valley.
    • I have done three trans-continental relocations.
    • I grew up in Kipling country – central India.
    • Along with English, I can speak four Indian languages - Hindi, Telugu, Bengali, and Bhojpuri