Drive data science projects that improve business revenue and productivity.• Set up a Python server environment for the development of data science projects and initiated the migration of projects to a newer cloud-based Azure Databricks machine learning platform. This enhanced team collaboration and accelerated productivity.• Partnered with the development and evaluation of a cross-sell model for the enterprise business that was incorporated into a sales application that guided sales strategy and resulted in millions of additional revenue opportunity.• Collaborated in the design and build of a QlikSense dashboard for spend analytics to understand employee spend patterns and quickly identify issues.

In Chief Technology Department, worked with a team to design and build a web-based application for interactive graph visualization. • Incorporated the web app into the internal Splunk-based security operations workflow, allowing analysts to select security incidents from a dashboard to visualize as connected graphs, and to interactively investigate incidents. • Created a workflow to search for phishing incidents and to visualize correlations with other events in Splunk.• Helped to plan and implement a complete code re-architecture that allowed the tool to efficiently scale to other use cases.

Performed advanced analytics to identify bookings opportunities and customer retention strategies.• Provided input and oversight for the design and implementation of a service-oriented personalization platform that integrates the eStore with SAS and Adobe Test and Target.• Identified key drivers of why a customer would stop using a product during its active subscription period. Built binary classification models to predict inactive customers and help the business target communication.

Performed analytical research and modeling. Extracted, created and organized data files for analytical and modelling purposes.• Helped develop logistic regression models that generated predictive scores/segments (propensity to purchase) for real time customer targeting.• Designed and implemented A/B tests and online marketing campaigns for a personalization pilot program.• Analyzed results of a loyalty pilot test to identify top value drivers that increase customer satisfaction and long-term sales and bookings.• Built a sequence of auto-regressive models that forecast visitors to the eStore based on PC shipments with preloaded trial software, enhancing marketing campaign strategies.• Built a binary classification model that predicts billing failure and identified key drivers for billing success. Incorporated results into the auto-renew dashboard and report.

Worked on a cross-functional team to launch a new consumer eCommerce platform to improve user experience and company revenue.• Helped to plan, strategize and manage the data preparation for the launches of 3 products and 10+ sites on the eStore.• Trained operations team to maintain data in the new platform and data stakeholders to troubleshoot potential problems.• Gathered requirements for and generated ad hoc reports to provide actionable insights.

Surrogate Models for Nonconventional Well Placement Optimization• Incorporated kernel learning methods for feature extraction into a genetic algorithm-based optimization problem• Performed data analysis using PCA, kernel PCA, cluster analysis, and support vector regression• Built data-driven, surrogate models for a high-fidelity simulator• Implemented a calibration scheme using the manifold mapping procedure

• Programmed Mica-type sensor motes using the Tiny Operating System (TinyOS) for a networked sensors project • Designed and conducted experiments to determine the sensitivity of light sensors to directionality and orientation

• Designed a program to model and analyze data from the simulation of a quantum semiconductor device • Compared two methods of function approximation, least squares fitting and a physics-based ‘particle’ method• Helped translate mathematical algorithms into C++ code, wrote prototype code, and tested the program for accuracy