nelsontodd

Built our order management system that was used for all production trading and forward testing. Could simultaneously manage all discretionary and algorithmic trading. Was used daily in production to manage a trading volume of up to ~$50mm/day and positions up to $8mm in options on equities. Micro service/client server architecture. - Built our real-time data system/real time feature generation system. This system was used for all research and all trading operations, both discretionary and algorithmic. I used fastapi to create a REST API that served as an interface to Interactive Brokers’ subscription feeds. Data from interactive brokers was then stored in redis for in memory delivery of live quotes, trades, bar data, and real time signal / feature generation to all of our research and trading efforts. I then wrote a small Python library to allow the rest of the team to use it in a few simple function calls. - EMSX (BBG’s FIX Wrapper), Redis, Pydantic, FastAPI, Redis, PostgreSQL, Celery, Docker.Northcut Trading was an algorithmic trading fund specializing in trading options on ETFs and other highly liquid equities. Owned by Dr Ed Bosarge. - Built our order management system that was used for all production trading and forward testing. Could simultaneously manage all discretionary and algorithmic trading. Was used daily in production to manage a trading volume of up to ~$50mm/day and positions up to $8mm in options on equities. Micro service/client server architecture. - Built our real-time data system/real time feature generation system. This system was used for all research and all trading operations, both discretionary and algorithmic. I used fastapi to create a REST API that served as an interface to Interactive Brokers’ subscription feeds. Data from interactive brokers was then stored in redis for in memory delivery of live quotes, trades, bar data, and real time signal / feature generation to all of our research and trading efforts. I then wrote a small Python library to allow the rest of the team to use it in a few simple function calls. - EMSX (BBG’s FIX Wrapper), Redis, Pydantic, FastAPI, Redis, PostgreSQL, Celery, Docker.

Trained a neural network to determine the minimizing coefficient of friction input for a torque and drag model, which models the axial drag along a drill string. Used DifferentialEquations.jl and flux.jl among other industry standard libraries. Mathematical Optimization, Machine Learning, Partial Differential Equations, Scientific Computing. Developed a Julia Library to reconstruct wellpath trajectories using B-Splines from a set of survey samples.