Vedant Choudhary
Business Analyst & Data Scientist
About Me
I'm a data scientist and business analytics professional with expertise in machine learning, statistical analysis, and business intelligence.
With experience at top companies like PwC, AbbVie, and Aetna, I specialize in transforming complex data into actionable insights that drive
strategic business decisions. My background spans from bioinformatics research to enterprise fraud detection and customer analytics.
On the weekends, I enjoy trying new cafes, cooking, running, playing basketball, and watching Formula 1 races.
Skills
Python
SQL
R
Machine Learning
AWS
Tableau
PowerBI
Model Deployment
A/B Testing
Data Storytelling
NLP
Recommendation Systems
PyTorch
Spark
Interests
Business Analytics
Data Science
Bioinformatics
Consulting
My Projects
Here are some of the projects I've worked on. Each one represents a unique challenge and learning opportunity.
Customer Analytics
Scalable Customer Interaction Analytics
Engineered Spark pipelines on AWS EMR to process large customer communication logs at scale. Delivered 50% improvement
in query runtime and deployed models to uncover customer behavior patterns.
Spark
AWS EMR
Python
ML Models
Fraud Detection
Enterprise Fraud Detection Capstone
Built supervised ML models (Random Forest, XGBoost) to detect anomalies and fraud in credit card transaction datasets.
Designed business reports interpreting fraud signals for non-technical stakeholders.
Random Forest
XGBoost
Python
Tableau
NPS Analytics
ThermoFisher NPS Prediction Model
Built supervised ML models to predict Net Promoter Score drivers using customer behavioral data. Developed interactive
Tableau dashboard with customer segmentation analysis and actionable business recommendations.
Gradient Boosting
Clustering
Tableau
Feature Engineering
FiTech
Data-Driven Credit Card Design
Developed an information-based strategy for FiTech's credit card product design. Optimized 12 different product variations
across 750,000 prospects using BK scores, APR, and annual fees to maximize Customer Lifetime Value and profitability.
Customer Segmentation
CLV Analysis
Risk Modeling
Product Optimization
S-Mobile
Predicting Customer Churn
Built predictive churn models using logistic regression and advanced ML techniques for Singapore's leading cellphone carrier.
Developed proactive retention strategies and quantified economic impact of targeted interventions across customer segments.
Logistic Regression
Churn Prediction
Customer Retention
CLV Analysis
Intuit
QuickBooks Upgrade Campaign
Analyzed response patterns from 75,000 businesses to predict likelihood of upgrading to QuickBooks 3.0. Developed targeting
strategies for wave-2 mailing campaigns to maximize conversion rates and optimize marketing spend efficiency.
Response Modeling
Campaign Optimization
Targeting Strategy
Marketing Analytics
