How does a quant trained in macroeconomics, corporate finance, and machine learning compete in today's global markets?
I aim to join a dynamic trading desk or asset management team where I can leverage my integrated background in quantitative and corporate finance, along with hands-on macroeconomic research, to develop and scale profitable trading strategies.
Prior to MSCF, my training covered the full spectrum: a quantitative economics track (GPA: 3.98) at Moscow State University-Russia's most prestigious institution-combined with rigorous finance and data analytics coursework at the New Economic School, HEC Paris, and Peking University. At the Central Bank of Russia, I developed inflation forecasting pipelines that now inform monetary policy. My modeling experience spans machine learning, deep learning, and econometrics-LSTM, Echo State Networks, Random Forests, PROPHET, SARIMAX, and more, applied to CPI forecasting and seasonal adjustment.
In parallel, I've spent considerable time working on valuation, M&A, and corporate finance, which gives me a strong grasp of business fundamentals behind market data. My fluency in Chinese and Russian also equips me to interpret and interact with emerging markets-an edge for global teams operating across geographies.
Let's connect-virtually or in person-so I can demonstrate how I'll bring value to your trading and investment team from day one.
