I am a Quantitative Researcher with a B.Tech in Computer Science from IIT Madras, combining strong technical skills with a deep interest in financial markets. At Squarepoint Capital, I build quantitative tools that enhance and systematize Fundamental Equity Research. I previously developed a prototype to capture discretionary analyst signals, which evolved into a scalable, multi-asset signal platform. My work includes collaborating on data pipelines for alternative datasets such as ownership structures and catalyst events. With experience as a Software Engineer at Amazon and proficiency in Python, C++, and Rust, I bring analytical rigor and a problem-solving mindset to quantitative finance.
Graduated from IIT Madras with a B.Tech in Computer Science and Engineering and CGPA 8.86.
Learned some basic but important topics like Linear Regression, Logistic Regression, Support Vector Machines, Unsupervised Learning, Anomaly Detection, Recommender Systems and Photo OCR.
Learned topics like Optimization Algorithms, Hyperparameter tuning, Batch Normalization and Tensorflow.
Learned topics like Computer Vision basics, Classic Networks, Residual Networks, Inception Network, Data Augmentation, Detection Algorithms, One Shot Learning, Siamese Network, Face verification and Recognition.
Please feel free to contact me for any project, big or small, I am always ready to be a part of your team.
London, United Kingdom