Shobhit Zakhmi

CEO

Bengaluru, Karnataka, India10 yrs 3 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in quantitative research and high-frequency trading.
Strong background in financial modeling and data analytics.
CFA Level 3 cleared, showcasing commitment to finance.

Stackforce AI infers this person is a Quantitative Finance expert with a focus on high-frequency trading and data analytics.

Contact

shobhitzakhmi1@gmail.com LinkedIn

Skills

Core Skills

Quantitative ResearchTradingQuantitative FinanceFinancial Modelling

Other Skills

Algorithm DesignAlgorithmsC++Counterparty Credit Risk ModellingData AnalysisData StructuresFunding ValuationHigh Frequency TradingMachine LearningMatlabMicrosoft ExcelMicrosoft OfficeMicrosoft PowerPointMicrosoft WordPowerPoint

About

Currently working as a Quantitative Researcher and Trader in High frequency Trading domain. Previously worked as a Quantitative Strategist for the Commodities desk in Securities Division at Goldman Sachs. Interested in Financial Markets, Financial Modelling and Data Analytics. Cleared CFA Level 3.

Experience

Plutus research private limited

4 roles

Vice President

Promoted

Aug 2025 – Present · 7 mos

Quantitative Research and Trading - High Frequency Trading in Indian Equity and Index Options (NSE)

Quantitative ResearchTradingHigh Frequency TradingData Analysis

AVP - Quantitative Research & Trading

Promoted

Aug 2023 – Jul 2025 · 1 yr 11 mos

Senior Quantitative Researcher

Promoted

Aug 2022 – Jul 2023 · 11 mos

Quantitative Researcher

May 2020 – Jul 2022 · 2 yrs 2 mos

Goldman sachs

Senior Analyst

Jun 2017 – Mar 2020 · 2 yrs 9 mos

Commodities Strategist (Securities Division)
Modelling of Counterparty Credit Risk and Funding Valuation for Oil/Metals/Nat Gas/Power Desks
Daily Attribution of PNL to various Greeks (Delta/Vega/Gamma/Theta/Rho) for Global Commodities Desk
Pricing of Metal Exchange Traded Derivatives for integration with the new Trader Web Interface

Counterparty Credit Risk ModellingFunding ValuationPricing DerivativesQuantitative FinanceFinancial Modelling

The university of british columbia

Research Intern

May 2016 – Aug 2016 · 3 mos · Vancouver, Canada Area

MITACS Globalink Programme in Computer Science
Topic: Vector Compression for Large scale Machine Learning
Improved runtime in state-of-the-art algorithm on Multiple Codebook Vector Quantization used at Google at that time
Added perturbations to Objective Function using Stochastic Relaxation to avoid Localised results obtaining higher recall
Paper published in ECCV 2018 titled “LSQ++: lower runtime and higher recall in multi-codebook quantization”

Indian institute of technology, delhi

Teaching Assistant

Jul 2015 – Jun 2017 · 1 yr 11 mos · New Delhi Area, India

Courses: Introduction to Electrical Engineering, Signals & Systems and Machine Learning

Eaton

Industrial Engineering Intern

May 2015 – Jul 2015 · 2 mos · Pune Area, India

Aerospace Group at SRSCOE (Safety, Reliability & Sustainability Centre of Excellence)
Topic: Failure Rate Characteristics estimation of AC Motor Hydraulic Pump at reduced voltages
Awarded Pre Placement Interview for exemplary performance