Aug 2024 – Present · 1 yr 8 mos · United Kingdom · Remote

• At QuantYog we are simplifying how to trade like quant/hedge funds. Whether you want to trade for yourself or work at a quant fund, you need to build a trading strategy that performs. That is what we teach.
• We have a highly efficient teaching methodology. Our courses have been rated 4.81 by our 100+ learners. Our learners work at Goldman Sachs, JP Morgan, Futures First, Coinbase, Paypal, Neo Wealth Management and other reputable firms. Our learners graduated from multiple IITs, IIMs, BITS, Columbia University and other stellar institutions.
• Our free on-demand webinar (quantyog.com/webinar) has been equally appreciated by complete beginners and also professional traders / quants with even 10 years of experience.
• We also offer paid consultations for those who value their time more than their money, and want to get to the great outcomes quant trading can provide significantly faster.
• You can find us at:
• Website - quantyog.com
• Instagram - instagram.com/quantyog
• Linkedin - linkedin.com/company/quantyog
• Reddit - reddit.com/user/QuantYog/submitted
• Youtube - youtube.com/@QuantYog

Aug 2023 – Jul 2024 · 11 mos · India

• Retired from the life of employment, and moved back to India for multiple reasons I documented here: quantyog.com/fire
• Spent most of this time managing personal wealth, developing my trading strategies, and automating my investment philosophy.

Apr 2022 – Jul 2023 · 1 yr 3 mos · London, England, United Kingdom

• Billion+ Google users make billion+ shopping queries daily across Google surfaces.
• I managed and led the team modelling and handling this rich data. This data is used for analytics, metrics, reporting, ML pipelines and debugging.
• We dealt with a massive amount of data that spans several years and amounts to petabytes. Our top priorities being complying with regulatory and privacy requirements, processing and managing the data in a cost-effective manner, and providing users with a fast and user-friendly interface for querying. Achieving these goals required masking the data's complexity, harmonizing the logging of data across various Google surfaces used by feature teams, and keeping up with the ongoing experimentation and changes happening on these surfaces.

Oct 2016 – Dec 2021 · 5 yrs 2 mos · London, United Kingdom

• One of the youngest Executive Director promotes at JP Morgan Chase & Co.
• Driving the industrialization of AI & ML within JP Morgan by delivering a consistent data analytics products implementation strategy to enable reuse of data analytics investments. Worked on transformation projects for the bank's post trade execution business which accounts for 30% of the workforce.
• Led the end-to-end build of EVA, an enquiry-virtualization automaton leveraging NLP and ML to automatically resolve hundreds of thousands of daily client queries. Conceived, delivered, and scaled the initiative from a single project into a full product, with a roadmap targeting $100M in annual savings for JPM. Built and led the team over multiple years, achieving $15M in realized annual savings by the time of departure.

Jul 2012 – Sep 2016 · 4 yrs 2 mos · India

• I received offers from Goldman Sachs, WorldQuant, PIMCO and a few other companies in Day 1 Slot 1 of IIT Delhi's campus placements. I chose to join Goldman Sachs' Quant/Strat role in Bengaluru as an Analyst. I was allocated to a Quant team heavily focused on Machine Learning and Data Science.
• Over the next couple of years I was quickly promoted to the next level (Associate) and was assigned as a team lead of 4 Quants handling ML/DS for a subdivision.
• During my time at Goldman I built products and worked on projects which benefited Goldman's bottomline to the tune of $10mn annualized.
• Due to the impact delivered at Goldman, I was able to transition from being an Associate at Goldman Sachs India to a Vice President at JPMorgan London.