I'm a Senior Consultant & Data Scientist at Varahe Analytics. My day-to-day involves building data platforms, analytics dashboards, and scraping systems that turn messy real-world data into something teams can actually make decisions with — social media metrics, salary benchmarks, engagement trends, campaign performance, all of it.
I've always been drawn to the problem-solving side of data. Understanding why something happened in a dataset, finding patterns nobody expected, connecting signals across platforms — that's the work I find most rewarding. Over the past few years I've gone deeper into LLMs and generative AI — building RAG pipelines, integrating OpenAI and Claude APIs into internal tools, experimenting with prompt engineering and fine-tuning to automate parts of the analysis workflow that used to be entirely manual.
I also build full-stack web applications — React frontends, Node/Express backends, MongoDB, the whole stack. It started because I needed better interfaces for the data tools I was building, and it stuck because I genuinely enjoy shipping things end to end. Outside of work, I'm usually reading about new developments in AI, contributing to side projects, or exploring how LLMs can be applied to domains beyond the obvious ones.
🔭 What I'm working on right now
- Building enterprise analytics dashboards that process data from Instagram, Facebook, YouTube & X
- Designing scraping systems with Playwright & Apify that don't fall apart at scale
- Shipping AI-powered sentiment analysis pipelines using Gemini for comment-level insights
- Building Facebook Ad Library intelligence tools for ad spend & impression reporting
- Exploring RAG pipelines and LLM-powered workflows for smarter data analysis
- Maintaining a salary prediction tool (Worthify.me) that uses ML to estimate developer compensation
Languages 
AI / GenAI / LLMs 
Data Science & ML 
Web & Frontend 
Scraping & Pipelines 
Databases & Infra 
📂 Projects
Most of my source code lives in private repos (client work), but I keep public showcases with documentation, architecture diagrams, and screenshots. Click through if you're curious:
| Project | What it does | |
|---|---|---|
| 🚀 | DataNautX | Enterprise social media intelligence — extracts and reports across FB, IG, YT & X |
| ⚡ | OmniMetric | Multi-platform social media intelligence pipeline — parallel fetching with auto-failover |
| 💬 | CommentLens | Comment extraction + Gemini AI-powered sentiment analysis across FB, IG, YT & X |
| 🏦 | AdVault | Facebook Ad Library intelligence — extract, analyze & report ad spend and impressions at scale |
| 🔗 | LinkLens | Multi-platform social media metrics extraction — paste URLs, get every metric |
| 📊 | SocialPulse Analytics | Automated analytics pipeline for social platforms using Streamlit + Google APIs |
| 🐦 | Twitter/X Scraper | Production-grade tweet & profile extractor built on Apify + Playwright |
| 💰 | SalaryLens | ML-powered salary prediction platform (Worthify.me) |
| 🧩 | CrossVerse | Superhero crossword puzzle game — full stack with auth, sessions & game logic |
📈 A bit about my background
I work at the intersection of data science and engineering. At Varahe, I've built 9+ production systems that:
- Scrape and process millions of social media data points across 4+ platforms
- Power real-time dashboards used by marketing and strategy teams
- Run AI-powered sentiment analysis on social media comments at scale using Gemini
- Extract and analyze Facebook ad library data for competitive intelligence
- Predict salary ranges using trained ML models
- Automate reporting pipelines that used to take days — down to minutes
Before getting deep into data science, I built full-stack web apps with Node.js and MongoDB — and I still enjoy that side of things. Having backend experience makes me better at building data tools that actually work in production, not just in notebooks.
📊 GitHub stats
Always happy to chat about data, AI, or interesting engineering problems — feel free to reach out.