Summary
Kohsheen Tiku is a Machine Learning Engineer based in the New York City area with 8 years of experience bridging software engineering and quantitative finance. He has built production ML and trading systems—from CNN-driven NLP at Samsung and high-performance data connectors at Magnitude to hierarchical reinforcement-learning portfolios at Bank of America and mid-frequency alpha strategies at WorldQuant (top 10 in the 2024 International Quant Championship). Comfortable shipping end-to-end solutions, Kohsheen combines C++/Java performance engineering with research-led ML and finance expertise developed during an NYU Financial Engineering masters. Now at Apexon, he focuses on applying rigorous statistical techniques and ML to real-world problems, bringing a practitioner’s attention to latency, robustness, and measurable risk-adjusted returns. An understated but consistent theme in his work is translating research prototypes into scalable, production-ready systems that materially improve performance metrics.
8 years of coding experience
3 years of employment as a software developer
Maths Physics Chemisty Economics English, Maths Physics Chemisty Economics English at AECS Magnolia Maaruti Public School - India
Master's degree Financial Engineering, Master's degree Financial Engineering at NYU Tandon School of Engineering
Bachelor of Engineering Computer Science, Bachelor of Engineering Computer Science at B. M. S. College of Engineering
Hindi, English