Verified recordFinancial Services

Alexandru-Petre Pitrop

Quantitative Modelling Senior Specialist at Lseg

Based in Bucharest, Romania

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Seniority

Other

Department

Other

Location

Bucharest

Industry

Financial Services

Company size

24K

Contact information

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Email

1 credit

a•••••••@lseg.com

Phone

5 credits

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Background

About Alexandru-Petre Pitrop

I am a motivated person who thrives at the intersection of finance and technology, where I blend my passion for quantitative analysis with solid programming skills in C++ and Python. I have worked as a Quantitative Developer at Phi Partners in Bucharest, where I have had the opportunity to engineer and work with many financial instruments. Each project has not only sharpened my technical abilities, but also deepened my understanding of market mechanics. My journey into quantitative finance began during my time at the University of Oxford, where I earned my MMath in Mathematics. The rigorous curriculum ignited my curiosity about how mathematical models can provide insights into market structure and enhance decision-making processes. Since then, I've been particularly fascinated by how Machine Learning can revolutionize algorithmic trading and quantitative research. I believe that leveraging data science tools can lead to smarter long-term predictions. Outside of work, I'm always eager to learn more about emerging technologies that shape our industry. Whether it's reading about new algorithms or participating in online forums discussing recent trends in quant finance, I'm dedicated to staying ahead of the curve. I also own 2 professional qualifications issued by the Romanian Ministry of Labour and Social Solidarity - for Photography and Cooking. In my spare time, I like to read and I am also a fan of many sports, such as table tennis, squash, badminton and, for the past 2 years, Latin dances. Feel free to connect if you feel inspired by my profile -). You can reach out to me directly on LinkedIn or via email: alex.pitrop24@gmail.com Skills: C++, Python, Data Science, Machine Learning, Quantitative Analysis

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