• CGPA: 3.70 (Dean's list)

• Activities: Co-authoring a comprehensive teaching manual for a Marketing Channel and Organization textbook, drafting in-depth case studies on B2B and B2C marketing channel strategies for over 30+ prominent firms as a Research Assistant at USC Marshall School of Business.
•USC Marshall's Business Analytics Student Association Ambassador

• Relevant Courses: Machine Learning, Deep Learning, Applied Statistics, Relational and non-relational Databases, Time Series Analysis, Forecasting, Data Analytics and Visualization, Business Analytics, Text Analysis and Natural Language Processing (NLP), Quantitative Investing, Product Management, Business Communication, Business Model for Digital Products

• Projects: High-Frequency Trading Model: A Challenge to the Random Walk Hypothesis
•Exploring the Impact of Different Audio Features on Predicting Song Popularity
•Zillow Property Price Prediction Model: Harnessing Data Analytics for Real Estate Valuation
•Regression Analysis on Dunnhumby Sales: Leveraging Transactions, Demographics, Marketing Campaigns, and Store-Level KPIs
•ASL Classification Using Transfer Learning: Advancing Sign Language Recognition

• CGPA: 8.75 (VITEEE Entrance Scholarship: Top 2% in 250,000 applicants)

• Activities: Team lead at Innovation Labs (VIT Bionest)
•Volunteer at Yash Vardhan Chartibale Trust to educate underprivileged children

• Relevant Courses: Python programming, Object Oriented Programming, Data Structure and Algorithms, Financial Econometrics, Operations Management

• Projects: Advanced Brain Tumor Detection and Classification using Watershed Segmentation and Convolutional Neural Networks
•Hybrid Ensemble Method for Solving the NP-Complete Traveling Salesman Problem
•Time-Series Stock Price Prediction Leveraging Long Short-Term Memory (LSTM) Networks

• Cross-Marketplace Visualization Dashboard Development: Developed and defined the business use case and unique selling proposition (USP) for a cross-marketplace visualization dashboard, leveraging web-scraped public data to provide insights on price tracking, product strategy, review sentiment analysis, and competitor benchmarking. Conducted SWOT analysis and identified 30+ marketplace KPI correlations to enhance the dashboard's value for eCommerce specialists, product managers, brand managers, SMB owners, and marketing teams, driving data-driven decision-making.

• Spearheaded decision analytics initiatives, leading a team to support B2B2C credit card services for multiple billion-dollar retailers. Engineered growth and marketing strategies, and facilitated ad-hoc root cause analysis for data-driven decision-making

Senior Business Analyst April 2021 - July 2023 • Customer Value Proposition and Customer Segmentation: Led a team of 5 to tailor Customer Segmentation for Marketing Campaigns driving 9.2% and 11.9% YoY sales growth on PL/CoB cards for 2 US retailers. Applied high-dimensional reduction and clustering algorithms in Python on Customer KPIs for a tailored marketing strategy (Earned Citi Gratitude Performance Award)

• Loyalty Point Forfeiture Classification and Forecasting: Executed a loyalty points redemption analysis, classifying behaviors (forfeited/redeemed) with Logistic Regression and forecasted forfeiture trends of at-risk accounts leveraging SARIMA using SAS and Python. Presented 2x points for at-risk accounts to mitigate NYS Senate 520E bill expected loss and re-engage customers

• APR Tier Adjustment Descriptive Analysis: Developed a competitive APR adjustment strategy for a major retailer, ensuring over 92% customer retention and generating an additional ~$90M in expected revenue. Achieved success from tier adjustments & Sales/Balance KPI analytics using SQL and Excel and presented visualization for stakeholder review, exceeding profitability goals

Business Analyst August 2021 - April 2023 • Cluster Analysis: Conceptualized campaign offers for Fortune 50 retailer, employing feature selection, K-means++ clustering, and cluster analysis with SQL and Python achieving ~72% higher sales versus proforma on credit cards

• Analytical Portfolio Deep Dive: Directed an in-depth analysis of a newly integrated retailer's 300k accounts portfolio. Pinpointed growth opportunities, identified Sales/Balance predictors via Regression in Python, evaluated past campaign offers, and conducted distribution analysis on KPIs, all aimed at informing future decisions (Awarded Citi Gratitude Performance Award)

• Omnichannel Engagement Strategy: Optimized Omnichannel strategy, employing advanced statistical tests for channel analysis, along with Regression Analysis in Python to identify purchase & balance patterns. Implemented targeted Credit Line Increases (CLI) to drive sales, attaining a significant 10% increase in sales and improved channel engagement

Technology Analyst April 2021 - August 2021 • Transaction Pipeline Automation: Enhanced Citi’s wallet transaction efficiency by automating 10 pipelines with AutoSYS watcher jobs & worked on OLTP data management PoC for reliable data routing and integrity across servers

• Delivered machine learning and analytics solutions for EXL’s healthcare client, dynamically targeting customers for campaigns

• Cancer Infographic Campaign Strategy: Spearheaded Cancer infographic campaigns targeting the cancer susceptible population by adopting an Ensemble Classification Model in Python with customer prescription and medical history embeddings. Visualized the insights and drafted 2 action plans to provide best-suited Infographic campaigns for EXL's US Healthcare Client (Fortune 500)

• Engineered a wireless haptic gear prototype that enhances virtual reality immersion by seamlessly transmitting sensor data from three CC2650 nodes to a Raspberry Pi. This data was transformed and visualized in real-time on a UNITY 3D model, under the mentorship of Professors Anand Bhojan, Chan Mun Choon, and Tan Wee Kek

• Developed a secure, smart city web-based book management system using Django, Raspberry Pi, and SQL. Leveraged Microsoft Azure IoT Hub to design an IoT dashboard for real-time monitoring and data distribution across the network, and utilized Power BI for comprehensive data analysis

• Co-author of a published chapter in Springer Lecture Notes in Electrical Engineering (2021), titled Tagging of Weakly Labeled Acoustic Data Using Skip Layer Connection Detection Classification Model.

• Developed an adaptive joint detection classification (JDC) model with skip-layer connections, enhancing neural network depth optimization for classifying weakly labeled acoustic data.

• Achieved a 17.19% error rate over the evaluation set, outperforming existing models like the Bag of Blocks (BOB) and standard JDC models.

• Implemented the model using advanced machine learning techniques like deep residual networks and stochastic gradient descent optimizers, demonstrating improved accuracy in audio tagging tasks.

• Utilized cutting-edge tools like the CHiME home dataset and Librosa signal processing library, gaining hands-on experience in acoustic scene and event classification.

• Published findings on neural network architecture optimization, contributing to the field of weakly labeled data classification in audio processing.

•Assisting Professor Gary Fraizer in the development of a comprehensive textbook on Marketing Channels and Organization, which includes in-depth exploration of channel strategy, organizational structure, and management practices. The textbook also covers franchising, channel functions, conflict management, partnership strategies, and other essential marketing topics.

•Co-authoring a Marketing Channel teaching manual with detailed case studies from prominent corporations in both B2B and B2C contexts for each chapter of the textbook. Additionally, contributing to the creation of supplementary teaching and learning resources to enhance the main textbook.