Rishav Sharma rvs23.dev

Rishav Sharma

I like to teach. I like to build.

Teacher, Palantir & AIP Engineer, Data Scientist in review

I hate randomness. I teach people to build on Palantir Foundry, and I like turning intuition into something you can measure. Away from the screen it's guitar and John Mayer, chess, GeoGuessr, and the occasional attempt at stand-up.

Work

Projects & learning

2026

Work

Projects & learning

Pet project in review

Hisaab, a finances tracker

Jun 2026

A local app for two people that replaced a finance spreadsheet and answers one question: did we invest what the plan said this year?

Code ↗

2025

Work

Ontologize in review

Palantir instructor & engineer

Aug 2025 → now

I teach Palantir Foundry and build with it: ontologies, pipelines and the applications on top.

Palantir Foundry Ontology Pipeline Builder Workshop AIP Teaching

2024

Work

Swiss Re GBS in review

Data Science Specialist II

Oct 2024 → Aug 2025

Promoted after two years. Data-science and language-model pipelines on Palantir Foundry for underwriting, operations and finance; underwriters about 30% more productive.

Palantir Foundry Python PySpark TypeScript SQL LLMs

Projects & learning

2023

Work

Projects & learning

2022

Work

Swiss Re GBS in review

Data Scientist I

Oct 2022 → Oct 2024

Joined Swiss Re's Global Business Solutions as a data scientist, building on Palantir Foundry.

Projects & learning

2021

Work

Projects & learning

2020

Work

Code-Young in review

Python instructor

Nov 2020 → Dec 2021

About 750 hours of live Python lessons for 25 students in India, the US and the UAE.

Projects & learning

University of Delhi · Hindu College in review

Master of Operational Research

Aug 2020 → May 2022

The mathematics of deciding under constraints: optimisation, queues, simulation and forecasting.

Optimisation Simulation Queueing theory Forecasting

2017

Work

Projects & learning

Osmania University · Bhavans College in review

B.Sc. in mathematics, statistics and computer science

May 2017 → May 2020

Three subjects side by side, which is close to the recipe for data science.

Mathematics Statistics Computer science