New York, New York, United States
Data Scientist & problem solver at the core, with a passion to improve businesses through data. Working at the Chief Analytics Office of IBM on opportunity identification & risk mitigation of IBM clients in GTS/SaaS/IaaS/PaaS domains (we won a Stevie award recently!). I am the tech lead for the Customer Analytics group Graduated with a MS in Data Science from Columbia University. Interned at Sam's Club, where, I improved forecasting of fresh produce sales by implementing an ensemble approach. Previously, worked as a Business Analyst for the Customer Experience team at Flipkart, India's leading e-commerce firm where I designed, analyzed and modeled on Customer Experience metrics(NPS, Resolution, Perfect Order and CS metrics) and spearheaded their drive by communicating the results to the Top management. I have an undergraduate degree in Engineering Physics from IIT Madras, IN. Data Science aside, I follow Cricket quite religiously, play table tennis, love to trek & travel, sip tea and read high-fantasy novels.
Building AI Agents for businesses
• Customer Analytics team aims at predicting & forecasting customer usage patterns in IBM businesses - SaaS, IaaS, PaaS, ISV • Developed multiple Classification & Time Series ensemble models to drive business impact • Lead a team of Data Scientists & Developers to improve & productionalize the models on IBM cloud • Drove business impact with CS, Marketing & product teams via. timely forecasts, predictions & alerts • The team won the coveted Stevie & TSIA STAR awards for innovation in Sales & XaaS management respectively
Founder and Lead, DSSE – Data Science Skills Enhancement • DSSE is a learning initiative aimed at imparting theoretical & practical ML knowledge to the CAO team • Led a team of 6 to conduct 50+ sessions; DSSE has had 2000 attendees with a NPS of 50% till date
Sales Forecasting for Fresh products • Implemented a Bayesian non-parametric model, Gaussian Process(GP), to predict sales with safety stock • Feature Engineered and built a stacked ensemble of GP, Neural Network & Gradient Boosting models • Achieved an improvement of 27% over existing time series methodologies, potentially saving $150M annually
Business Analyst in Customer Experience team In-short: Designed, owned, analyzed and modeled on Customer Experience Metrics(NPS, Resolution, Perfect Order and CS metrics) and spearheaded their drive in tandem with product, operations and the top management Top Projects: 1. Net Promoter Score(NPS) framework (Tools: Python, SQL, Hive, QlikView) • Developed logistic regression and random forest models, achieving a best F-score of 85% • Established impact of Delivery time, Product quality and Customer Support on Customer Retention • Created an actionable dashboard on QlikView for tracking and preliminary analysis • Spearheaded NPS growth strategy through focus on Supply Chain; Improvement of 15% in NPS 2. Customer Satisfaction(CSAT) Framework (Tools: R, SQL, QlikView) • Identified key Business and Operational drivers through a comprehensive LDA Topic Model on customer inputs • Provided comprehensive analysis of “topics” driving Resolution, leading to a 20% organic improvement 3. Customer Escalations and Issues (Tools: Python, SQL) • Feature engineered “Customer anxiety”, “Order anxiety” & “Perfect Order” through EDA of customer escalations • Developed a Random Forest Model, prioritizing 5% of 2M monthly customer issues and preempting 68% escalations • Built an analytical framework to define rules to route customers through IVR, reducing call volumes by 26% 4. Metric Design and Analysis (Tools: SQL, Hive, QlikView) • Designed, analyzed and owned customer experience metrics: NPS, Perfect Order, CSAT • Measured and established impact of metrics on Customer Retention and growth(TPC) • Monitored health of metrics periodically and performed in-depth RCAs on changes