Kshitij Sharma

I’m a self-taught data analyst and the creator of DataLab, an open-source Python library designed to diagnose and clean extremely messy, real-world datasets.

I left my previous role to work full-time in data because I realized that many analytics and ML failures come from blind data handling rather than poor modeling - and I wanted to solve that problem at the foundation.

DataLab is built around a simple idea: different types of data require different ways of thinking.

I’ve implemented type-aware workflows for numerical, text, and datetime data, along with detailed diagnostics that surface why data looks the way it does — including tracking values that silently fail cleaning operations.

The library is stress-tested on intentionally dirty datasets that resemble real production data, not curated tutorials.

My background includes 7+ years in customer-facing roles including 2.5 years at American Express, where I developed strong analytical reasoning, pattern recognition, and stakeholder communication skills in high-impact, regulated environments. That experience strongly influences how I approach data: carefully, transparently, and with attention to real-world consequences.

I’m especially interested in roles involving data quality, analytics, reporting, and decision support.

I enjoy working close to raw data, documenting assumptions, and building workflows that others can trust and understand.

I value clarity over cleverness, correctness over speed, and learning through building.