Anshumaan Gandhi

CEO

Chicago, Illinois, United States6 yrs 10 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Founded an investment advisory company managing $500k AUM.
Pioneered advanced quantitative models during internship at JPMorgan.
Pursuing a master's in Financial Mathematics for quantitative trading.

Stackforce AI infers this person is a Fintech professional with strong quantitative analysis and trading expertise.

Contact

Skills

Core Skills

Quantitative AnalyticsModel Risk Management

Other Skills

Artificial Intelligence (AI)Bayesian Tobit RegressionC++Data AnalyticsData MiningData ScienceEquity DerivativesEquity TradingInvestmentsJavaLASSO frameworkModel Risk GovernancePython (Programming Language)Quantitative modelsResearch

About

Anshumaan is passionate about applying computational and analytic tools to the equity markets. He refined his toolkit during his undergraduate studies in Computer Science and internship experiences, then started his own investment advisory company, with 14 clients and an AUM of $500k. Aspiring to move beyond the legacy tools of finance, he is pursuing a masters in Financial Math to apply cutting edge quantitative methods and machine learning to the equity markets. Upon completion, he aspires to a career as a quantitative analyst/trader.

Experience

Belvedere trading, llc

Quantitative Trader

Jan 2025 – Present · 1 yr 2 mos · Chicago, Illinois, United States · On-site

Chicago trading company

3 roles

Quantititative Trader

Apr 2024 – Nov 2024 · 7 mos

Options Market Making - European Indexes
DAX | SX5E

Quantitative Trading Analyst

Jul 2023 – Mar 2024 · 8 mos

Options Market Making- Eurostox

Quantitative Trading Analyst

Feb 2023 – Jun 2023 · 4 mos

Options Market Making - Crude Oil

Jpmorgan chase & co.

Quantitative Analytics Summer Associate

Jun 2022 – Aug 2022 · 2 mos · New York, New York, United States

Interning as a part of the Model Risk Governance and Review team covering quantitative models for credit risk products.
Pioneered a Bayesian Tobit Regression model for benchmarking and validating existing LGD models for CMBS portfolios.
Implemented a LASSO framework on the same for efficient feature selection while retaining model interpretability.
Reviewed quantitative models and wrote documentation eliciting model usage, justification as well as validation.

Bayesian Tobit RegressionLASSO frameworkModel Risk GovernanceQuantitative modelsQuantitative AnalyticsModel Risk Management