I specialize in designing and scaling ETL pipelines, data automation, and machine learning integrations — bridging the gap between business needs and technical execution.
I strongly believe in the quote: "You become what you believe." With a can-do attitude and a passion for continuous learning, I thrive on solving complex data challenges and building impactful solutions. Beyond my technical work, I'm passionate about building a global, data-driven community, mentoring peers, and sharing knowledge through talks, blogs, and open-source contributions.
- 🛠️ ETL Development & Data Pipeline Optimization
- 🤖 Machine Learning Deployment & Integrations
- 📊 Data Modeling & Quality Assurance
- ☁️ Cloud Data Infrastructure (AWS & Azure)
- 🔄 Streaming & Real-time Data Processing
- 🥇 TextNow AI Hackathon 2025 — Winner
- Built an AI-powered support assistant that classifies user questions against Slack history, suggests relevant past answers, and escalates unmatched queries via chatbot to Jira with contextual ticket creation.
AI-powered support assistant that classifies questions against Slack history, suggests relevant answers, and escalates to Jira with contextual ticket creation.
- Stack: AI, NLP, Slack API, Jira, Chatbot
Analyzed the impact of mandatory calorie labeling on restaurant menu choices using causal inference and statistical modeling.
- Stack: Python, Causal Inference, Statistics
Web analytics dashboard tracking recruiter engagement patterns on LinkedIn profiles using web scraping and data visualization pipelines.
- Stack: Web Scraping, Analytics, Visualization
Applied supervised ML models (Random Forest, SVM, XGBoost) on Chicago crime dataset, achieving 85%+ classification accuracy.
- Stack: Scikit-learn, XGBoost, Machine Learning
Amazon Alexa skill that recites couplets from the ancient Tamil classic Tirukkural, with contextual explanations and keyword search.
- Stack: Alexa SDK, Node.js, NLP
NLP pipeline that crawls major news outlets, applies sentiment analysis and topic modeling, then surfaces a daily "optimism score."
- Stack: NLP, Sentiment Analysis, NLTK
Computer vision system for monitoring patient activity and posture in clinical settings using image classification.
- Stack: Computer Vision, TensorFlow, Healthcare
- 🎓 Master of Science in Computer Science | Illinois Institute of Technology, Chicago (2016–2018)
- GPA: 3.72 / 4.0 | Concentration in Data Science, Software Engineering & Database Systems
- 🏆 TextNow AI Hackathon 2025 Winner
- 🎤 PyData Chicago Speaker (June 2018) — Text mining & causal inference research
- 🌐 NumFOCUS Guest Speaker — Open-source scientific computing community outreach
- 🧠 ML with TensorFlow on GCP Specialization — Google Cloud / Coursera
- 🔬 Art and Science of Machine Learning — Google Cloud / Coursera
- ⛏️ Mining Massive Datasets — Stanford University
- 📊 Statistical Learning — Stanford University
- 🧬 Neural Networks and Deep Learning — deeplearning.ai / Coursera
"If you hang around the barbershop long enough… sooner or later you're gonna get a haircut." — Denzel Washington