Kohsheen Tiku

Machine Learning Researcher at PIK - Potsdam Institute for Climate Impact Research

Abu Dhabi Emirate, United Arab Emirates
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Summary

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Senior
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Top School
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.
code8 years of coding experience
job4 years of employment as a software developer
bookMaths Physics, Maths Physics at AECS Magnolia Maaruti Public School - India
bookMaster's degree Financial Engineering/ Applied Math, Master's degree Financial Engineering/ Applied Math at NYU Tandon School of Engineering
bookBachelor of Engineering Computer Science, Bachelor of Engineering Computer Science at B. M. S. College of Engineering
languagesHindi, English
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Github Skills (37)

kubernetes10
security10
golang10
rust10
cloud-native10
linkerd10
api-client9
hub9
service-mesh9
huggingface9
go9
minikube9
google-colab8
machine-learning8
inference7

Programming languages (6)

TypeScriptJavaScriptVueGoJupyter NotebookPython

Github contributions (5)

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kohsheen1234/instagramclone

Feb 2018 - Jul 2018

Contributions:3 commits, 2 pushes, 1 branch in 5 months
Contributions:1 push, 1 branch in 2 years 6 months
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