Quantitative Research

Fellowship Program

Six month machine learning training. Advance your career to the next level. 

The Program

Gain the experience necessary to succeed in high tech, quantitative research, or data science positions. Implement real world machine learning problems, publish findings, land a position with top firms.

Fellows come from top universities and often complete non-computer science PhD. They pursue technology, data and quantitative research roles. 

Benefits:

Learn how to solve problems in quantitative finance

Needs based scholarships available

Research state of the art learning algorithms

Develop skills sought by top tech and quant firms

Program support till you receive a full time job offer

Network with previous Algo Depth quants

 
 
Reinforcement Learning

Research in policy gradient, actor critic, and Q learning algorithms. Use cases include order execution, alpha generation, and asset allocation. 

Deep Learning

Primary focus on convolutional and recurrent neural networks used in alpha generation and feature selection.  

Signal Processing

Better estimate future prices by decomposing trends. Wavelet and Fischer Transform, among others, used to predict equity markets.  

ALGO DEPTH RESEARCHERS GO ON TO WORK AT TOP FIRMS

QUANTITATIVE RESEARCH
INVESTMENT BANKING
TECHNOLOGY
Xiao Shi
Princeton PhD, Computational Chemistry
Quantitative Researcher - Barclays
Isaac Chen
Brown PhD, Computational Physics 
Machine Learning Engineer Intern - Twitter
Zixuan Zhang
Cornell Masters, Chemical Engineering 
Software Developer - Uber
Yuan Sun
Columbia Masters, Operations Research
Quantitative Associate - Morgan Stanley

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We collaborate with ambitious companies and individuals; let's build something great together.

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