Aryamaan Srivastava

WORK HISTORY

EDUCATION

ABOUT ARYAMAAN SRIVASTAVA

I’m a data scientist and software engineer working at the intersection of machine learning, statistics, and large-scale data-driven decision systems, with a strong interest in both financial modeling and real-world analytics problems.I’m currently pursuing an M.S. in Data Science at Columbia University, where my work focuses on applied machine learning, time-series forecasting, causal inference, and stochastic processes. As a Research Assistant, I’ve worked on projects ranging from testing the Efficient Market Hypothesis using ML techniques to forecasting and causal analysis on large urban datasets, translating statistical insights into practical conclusions.Previously, I worked at Société Générale as a Software Engineer and later as a Specialist Software Engineer in Quantitative Risk. My work involved building predictive and scenario-based models for financial metrics, developing scalable Spark-based data pipelines on cloud infrastructure, and designing ML-driven monitoring systems that significantly improved reliability and response times across global production systems.My interests span time-series modeling, reinforcement learning, econometrics, and predictive analytics, and I enjoy tackling problems where modeling rigor, scalability, and decision impact all matter. I’m particularly drawn to roles and collaborations that combine strong mathematical foundations with modern machine learning and real-world deployment.I’m always open to connecting and collaborating on projects involving machine learning, forecasting, quantitative research, or applied data science.