Quantitative Researcher, RBC Capital Markets, LLC, New York, NY

Conduct quantitative research on algorithmic trading, routing mechanisms, and trading costs.,Analyze global markets and alternative data sources using kDB+/Q and Python.,Build ETL pipelines for out-of-core / big datasets using Python.,Leverage expertise in time series, signals processing, and statistical inference to estimate various characteristics of market data.,Provide key insights and support for the sales and trading team by instrumenting metrics and implementing monitoring / alerting tooling.,Leverage expertise in deep learning frameworks such as PyTorch to integrate state of the art algorithms and artificial intelligence tools with trading algorithms.

Master's degree in Computer Science, Financial Engineering, Mathematics, Physics, or a related field,3 years of experience in writing software in Python to design, maintain and operate batch and stream processes for model fitting and inference pipelines (including metrics, monitoring, and alerting).,3 years of experience in kDB+ / Q for conducting statistical analysis on large datasets.,3 years of experience in equity algorithmic trading to produce models that will be consumed by algorithmic trading software.,3 years of experience in quantitative research, modelling (time series, linear models).,3 years of experience in applied machine learning, and data visualization.,3 years of experience in global equity markets and microstructure.

Master's Degree