Open to opportunities

Vedran Raca

@vedranraca

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VP model developer with expertise in quantitative finance and machine learning.

Poland

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What I'm looking for

I seek a challenging role in quantitative finance that fosters innovation and growth.

With over 5 years of experience in quantitative finance, I have honed my skills as a VP model developer and validator, specializing in algorithmic trading and counterparty risk models. My academic background includes a Master's in Quantitative Finance and another in Theoretical Physics, equipping me with a robust analytical framework to tackle complex financial challenges.

Currently, I am leading the development of machine learning-driven hedging strategies at BNY Mellon, where I have successfully implemented a deep hedging framework that utilizes neural stochastic differential equations. My previous roles at Citi Bank and UBS involved rigorous model validation and risk assessment, ensuring the robustness and reliability of trading models. I am passionate about continuous improvement and delivering high-quality results in fast-paced environments.

Experience

Work history, roles, and key accomplishments

Current

VP, Quantitative Analyst

Current

BNY Mellon

Apr 2024 - Present (1 year 2 months)

Developed and implemented machine learning-driven hedging strategies using Neural Stochastic Differential Equations. Created a data-driven deep hedging framework for pricing and hedging derivatives in incomplete markets with real market data.

Python Machine Learning Neural Networks Stochastic Differential Equations Derivatives Data Analysis

AVP, Quantitative Analyst

Citi Bank Europe

Jun 2022 - Mar 2024 (1 year 9 months)

Reviewed algorithmic trading models related to market-making in FX. Conducted comprehensive validation involving model risk assessment and implemented challenger models.

Validation Algorithmic Trading Risk Assessment Data Analysis Python

Quantitative Analyst

UBS Bank

Nov 2019 - May 2022 (2 years 6 months)

Assessed CCR/XVA models for conceptual soundness and robustness. Conducted tests in Python, including benchmarking and stress testing, while documenting findings in validation reports.

Validation Python XVA Risk Management Data Analysis Documentation

Quantitative Analyst

Deutsche Borse Group - Clearstream Banking

Feb 2019 - Dec 2019 (10 months)

Designed and improved financial risk models in Python to manage risk exposure and concentration risk effectively.

Risk Modeling Python Risk Management Data Analysis Quantitative Analysis

Scientific Researcher Assistant

Institute of Physics, Belgrade

Nov 2016 - Dec 2018 (2 years 1 month)

Conducted research in excitonic physics within graphene quantum dots, contributing to scientific understanding in the field.

Research Excitonic Physics Quantum Dots Data Analysis Collaboration

Education

Degrees, certifications, and relevant coursework

University of Belgrade, Faculty of Economics

Master of Science, Quantitative Finance

Completed a Master of Science in Quantitative Finance with elective courses in Advanced Risk Modelling, Financial Derivatives, and Fixed Income. The master thesis focused on the application of machine learning for pricing Hawaiian options, comparing various models including Random Forest and DNN.

University of Belgrade, Faculty of Physics

Master of Science, Theoretical and Experimental Physics

Achieved a Master of Science in Theoretical and Experimental Physics, with elective courses in Statistical Physics, Statistical Quantum Physics, and Mathematical Physics.