Steven Maharaj
Quantitative Trader at CryptoProp- Claim this Profile
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Bio
Credentials
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Akuna Capital Options 101
Akuna CapitalAug, 2020- Sep, 2024 -
Market Regulation
CME GroupAug, 2020- Sep, 2024 -
Working Remotely
LinkedInApr, 2020- Sep, 2024 -
React.js Essential Training
LinkedInMar, 2020- Sep, 2024 -
Test-Driven Development in Django
LinkedInMar, 2020- Sep, 2024 -
Building a Personal Portfolio with Django
LinkedInJan, 2020- Sep, 2024 -
Deploying Django Apps: Make Your Site Go Live
LinkedInJan, 2020- Sep, 2024 -
Introduction to Trading, Machine Learning & GCP
CourseraJan, 2020- Sep, 2024 -
Learning C++ Pointers
LinkedInJan, 2020- Sep, 2024 -
Learning Django
LinkedInJan, 2020- Sep, 2024 -
Data Science and Machine Learning Bootcamp with R
UdemyDec, 2019- Sep, 2024 -
Deep Learning with Python and Keras
UdemyDec, 2019- Sep, 2024 -
Django: Forms
LinkedInDec, 2019- Sep, 2024 -
Faster Python Code
LinkedInDec, 2019- Sep, 2024 -
Microsoft Excel - From Beginner to Expert
UdemyDec, 2019- Sep, 2024 -
Python Algo Stock Trading: Automate Your Trading!
UdemyDec, 2019- Sep, 2024 -
Python for Financial Analysis and Algorithmic Trading
UdemyDec, 2019- Sep, 2024 -
Quantitative Finance & Algorithmic Trading in Python
UdemyDec, 2019- Sep, 2024 -
Managing Your Personal Finances
LinkedInJun, 2018- Sep, 2024
Experience
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CryptoProp
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Australia
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Financial Services
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1 - 100 Employee
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Quantitative Trader
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Oct 2020 - Present
Development and management of trading systems. Code development for Quantitative trading and research. Development and management of trading systems. Code development for Quantitative trading and research.
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Lesson Up
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Professional Training and Coaching
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Teacher
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Jan 2020 - Oct 2020
My own tutoring business https://lessonup.com.au/ My own tutoring business https://lessonup.com.au/
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Ecole Centrale de Paris
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France
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Civic and Social Organizations
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Research Assistant
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Jan 2019 - Apr 2019
Using likelihood estimation techniques a model was created to predict the intensity of market ask and market buy orders. In terms of data analysis, I worked with the 'limit order books' of several liquid stocks. All computations were performed in R or Python. Using likelihood estimation techniques a model was created to predict the intensity of market ask and market buy orders. In terms of data analysis, I worked with the 'limit order books' of several liquid stocks. All computations were performed in R or Python.
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University of Melbourne
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Australia
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Higher Education
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700 & Above Employee
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President Statistics and Mathematics Postgraduate Society
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2018 - 2019
This society aims to sustain a sense of community among postgraduate students in the school of mathematics.
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Mathematics Tutor
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Jan 2017 - Nov 2018
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President Street Workout and Calisthenics Club
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2017 - 2018
University of Melbourne Calisthenics Club started with myself and my predecessor to promote free/cheap fitness at the University of Melbourne.
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Education
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2017 - 2019
University of Melbourne
Master of Science (M.Sc.), Mathematics -
2014 - 2016
University of Melbourne
Bachelor of Science (BSc), Mathematics
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