Vishnu Vijayakumar (he/him)

Designed a control module for monitoring Date of First Delinquency reporter to credit bureaus achieving a 100% DA RTE reduction & saving nearly 400 man hours(monthly) in manual validations Built an analytical data layer for YACC NLP model to help unlock cross channel insights that will inform future servicing strategy saving 200+ hours of analyst time, monthly, in call analysis efforts Devised a data quality module in Pyspark for Capital one’s in house production migration platforms to run automated data validations, increasing speed to market by 80%

Implemented an enterprise level presentation layer to serve as the source of truth for Card CEMP data standardizing NPS reporting and eliminating 90% BA RTE across partner teams Designed a fully automated Agent Scorecard platform catering to 3000+ call center agents enabling continuous performance monitoring and management, saving 600 monthly hours of manual work for individual teams Orchestrated a datamart to facilitate customer experience monitoring for teams within US Cards, combining several disparate data sources, drastically reducing overall data complexity and saving 300+ monthly man hours

• Defined a virtual care brand strategy for PSH through audience identification for consumers who would be candidates for virtual care offerings surrounding the PSH system • Leveraged patient data and demographic information to build patient personas around 5 major TJR services offered by TCH to understand the present consumer profile and devise strategies around top MSK services offered as part of the new brand campaign • Performed customer profiling and segmentation for Henry Ford in the state of Michigan to identify population segments who might not be inclined in following COVID safety protocols leveraging attitudinal and soci0-economic attributes • Collaborated with JHM Planning team to understand consumer sentiments on virtual care and services offered by JHM against major competitors to personalize marketing strategies by conducting surveys and leveraging consumer sociographic and psychographic information

• Created and implemented several reporting solutions in Tableau and PowerBI, for enhanced data tracking and assessment of awards, grants and proposals for different colleges within the university • Developed a TS forecasting model using LSTM to predict the number of awards and grants the university would receive in the coming fiscal year achieving a decrease in MAE by 42% over the previous best model

Data diagnostics and storytelling • Designed data warehousing solutions for a Fortune 500 company in Azure cloud services using ADF and SQL Server and reporting solutions in Tableau to support ad hoc business analysis • Streamlined and automated an end-to-end solution for a UK client using SQL and Alteryx aimed at providing reporting solutions in Tableau for optimized revenue planning eliminating manual intervention by 80% • Employed JavaScript and python modules in Spotfire to develop a sophisticated scoring algorithm to tag and track high risk transactions across 70+ markets for a US client enabling an overall 21% annual cost reduction Statistical analysis and Machine Learning • Performed data cleaning, hypothesis testing, exploratory data analysis and ML model building in Python for a real estate client to generate key insights and recommendations for their latest business model • Devised and evaluated multiple machine learning models such as Logistic Regression, GLM, Random Forests, XGBoost and Neural Networks to predict possible credit card defaulters for a UK bank enabling a 32% savings in annual revenue figures • Managed a 7-member team and coordinated with several C-suite executives in developing a clustering module in R to optimize distribution network operations achieving 11% improvement in annual returns Big Data and Deep Learning • Guided a 6-member team, developing forecasting modules for demand response in Azure Databricks using SparkR for analysis of day to day power consumption patterns of US households for a P&U firm • Implemented NLP for classification of customer complaints for an IT services client processed using Apache Spark leveraging deep learning techniques to identify major areas of concerns and allocate resources to reduce resolution costs by 27%

• Collaborated with a 5-member cross functional team to create a hospitality dashboard in Tableau with SAP HANA source system for a hotel chain to monitor key metrics such as RevPAR, ADR and ROH to develop actionable insights • Created workflows in Alteryx for cleaning and transforming data from various source systems for modelling and developing reporting solutions in Tableau for a US real estate client to generate key insights and recommendations for their latest business venture • Developed Tableau dashboards to enhance the existing reporting solutions in SAP BO for an IT services client who wanted to monitor their operations and identify pain points through key metrics such as ticket volume, backlogs, avg resolution time, CSAT etc. achieving an increase in ticket resolution by 27% in the first quarter

Relevant Coursework 1) Machine Learning 2) Advanced Data Mining 3) Big Data Integration 4) Time Series and Forecasting 5) Statistical Methods and Analysis 6) Statistical Computing using SAS 7) Probability Models and Statistics 8) Optimization 9) Data Visualization with Tableau 10) Data Management with SQL 11) Linear Regression 12) Data wrangling with R

Relevant Coursework: Operations Research Supply Chain Management Data Analysis and Optimization System Modeling & Simulation System Dynamics Heuristics for Decision Making Stochastic Models Marketing Management Engineering Mathematics - I,II,III