Ganesh .

CEO

Bengaluru, Karnataka, India3 yrs 9 mos experience

Key Highlights

Master's in Data Analytics and Decision Science.
Developed advanced quantitative models for finance.
Experienced in machine learning and optimization.

Stackforce AI infers this person is a Fintech professional specializing in quantitative analysis and financial modeling.

Contact

Skills

Core Skills

Quantitative Investment StrategiesComputational FinanceMathematical ModelingData Analysis

Other Skills

Black Scholes ProcessC#C++Commodity ContractsCorrelated Heston Path GeneratorData StructuresDerivativesElectricity PricingFinancial MarketsHeston ProcessInvestment StrategiesMachine LearningMathematical ModelsMonte Carlo SimulationOptimization

About

I have completed my Master’s in Data Analytics and Decision Science from RWTH Aachen and a B.Tech in Computer Science (top 5% of class). I'm skilled in computational finance, financial markets, data analysis, Python, C#, machine learning, and optimization. I currently work at HSBC as an AVP in Quantitative Investment Strategies, aiming to grow as a focused and detail-oriented Quantitative Researcher. Areas of Interest : Reinforcement learning, Optimization Models for Finance, Stochastic Calculus

Experience

Hsbc

Assistant Vice President - Quantitative Investment Strategies (QIS)

Apr 2025 – Present · 11 mos · Bengaluru, Karnataka, India · Hybrid

Quantitative Investment StrategiesComputational Finance

Allianz global investors

Intern - Quantitative Investment Strategies ( QIS )

Jul 2024 – Dec 2024 · 5 mos · Munich, Bavaria, Germany

Developed a Quantitative Library Toolkit for use in Quantitative Investment Strategies.
Developed a Generic Volatility Class that provides All information regarding Volatility Surface, Smile Sections, Variances, Risk Reversal and Butterfly Calculations of the FX Options
Developed a Monte Carlo Simulation Functionality that is used by Stochastic 1D processes for Path Generation, Pricing of Paths and Calculating the final expected Payoff. Extended the Functionality for Pricing Paths using Heston and Black Scholes Processes.
Worked on understanding the existing Investment Strategies focused towards managing Tail Risks and perform hedging using Derivatives
Created a Correlated Heston Path Generator and Pricer using Cholesky decomposition. Explored different Discretization schemes as a part of the task.

Quantitative Library ToolkitVolatility ClassMonte Carlo SimulationStochastic ProcessesHeston ProcessBlack Scholes Process+5

Rwe

Working Student - Commodity and Asset Modelling

Jan 2024 – Jun 2024 · 5 mos · Essen, North Rhine-Westphalia, Germany · Hybrid

Supported the development of Mathematical Models for Renewables and Hydrogen asset portfolios (Wind, Solar), as well as for commodity contract portfolios including (e.g. gas and electricity options, spread options) for the European and Australian Markets.
Developed a Generalized Additive Machine Learning model for predicting the prices of Electricity across 4 Australian Regions.
Developed a Python Mathematical Model for predicting the Payoffs of Spread Options using Margrabe's Formula.

Mathematical ModelsMachine LearningPythonElectricity PricingCommodity ContractsMathematical Modeling+1