Arnav Garg

Associate Consultant

Mumbai, Maharashtra, India5 yrs 9 mos experience

AI EnabledAI ML Practitioner

Key Highlights

5+ years in Quantitative Finance
Expert in systematic strategy development
Proficient in advanced analytical tools

Stackforce AI infers this person is a Quantitative Finance expert with strong capabilities in both Commodities and Credit trading.

Contact

Skills

Core Skills

Quantitative FinanceCommodities TradingCredit TradingData AnalysisPredictive ModelingMachine LearningNatural Language Processing

Other Skills

AlgorithmsBond Trading AnalyticsCC++Capacity Forecasting ModelChatbot DevelopmentCommunicationCredit Curve ModelingData StructuresGitJavaML regression modelsPortfolio Risk ManagementPythonRisk Factor Eligibility Modelling

About

IIT Kanpur graduate with 5+ years of experience in Quantitative finance, currently working as a Strat at Morgan Stanley in the Commodities division, having previously worked as a Quantitative Researcher with J.P. Morgan Chase & Co. in the Credit division. Experience in systematic strategy development, analytical tools and pricing models.

Experience

Morgan stanley

Quantitative Researcher

May 2023 – Present · 2 yrs 10 mos · Mumbai, Maharashtra, India · On-site

Commodities Front Office Desk Strategist
Power & Gas and Agriculture markets
Volatility Calibration / Modelling
Structured product analytics
Indicative pricing
Risk Factor Eligibility Modelling

Volatility CalibrationStructured product analyticsRisk Factor Eligibility ModellingQuantitative FinanceCommodities Trading

Jpmorgan chase & co.

Quantitative Researcher

Jul 2020 – May 2023 · 2 yrs 10 mos · Mumbai, Maharashtra, India · On-site

Credit Front Office Desk Strategist
Bond Trading Analytics
Credit Curve Modeling
Hedging / Trading Strategies
Portfolio Risk Management

Bond Trading AnalyticsCredit Curve ModelingPortfolio Risk ManagementQuantitative FinanceCredit Trading

Fidelity investments

Capital Markets Analyst

May 2019 – Jul 2019 · 2 mos · Bengaluru, Karnataka

Built a Capacity Forecasting Model, which, based on historical market trends/factors and app/server utilization trends, predicts the future app utilization demands.
Used Time-series forecasting techniques like ARIMA, Holt-Winter’s Model for finding error, seasonality, auto-correlation and trends in the data.
Applied ML regression models like Linear regression, RANSAC, AdaBoost, Random Forest etc. between market factors and Avg. CPU utilization for predictive analysis.

Capacity Forecasting ModelTime-series forecastingML regression modelsData AnalysisPredictive Modeling

Treadwill

Machine Learning Intern

May 2018 – Jul 2018 · 2 mos · Kanpur, Uttar Pradesh

Built a Chatbot which communicates with depressed people using Natural Language processing.
Used Pytransitions to build a FSM model to facilitate conversation. The framework was built on RASA NLU, using ML algorithms for intent/entity classificartion.
Coded chat modules for the chatbot to facilitate task oriented conversations, using CBT.

Natural Language ProcessingMachine LearningChatbot Development