R Performance Engineer (Sports Analytics Simulation Optimization) - Part-time /Fulltime - Worldwide

Looking for an experienced R engineer to help optimize and scale a proprietary simulation platform used in daily fantasy sports contest play and sports betting. This role focuses on improving the performance of R-based simulations, lineup optimizers, and data pipelines that support real-time lineup decisions and strategic testing.

You'll be responsible for speeding up simulation runtimes, reducing memory usage, improving I/O performance, and automating key workflows. This is a hands-on role focused on execution and quality.

Key Responsibilities:

•	Profile and optimize R simulations for speed and memory efficiency
•	Refactor legacy scripts using modern practices
•	Streamline file I/O, parallel computing, and simulation batch processing
•	Help modularize and clean up core infrastructure code
•	Collaborate on data pipeline and logic improvements

Requirements:

•	Expert-level R experience (especially data.table, dplyr, lpSolveAPI, profiling tools)
•	Strong background in simulation-heavy or optimization-driven systems
•	Comfort with async development, clean documentation, and working from specs
•	Highly reliable, detail-oriented, and performance-minded

Nice to Have:

•	Experience in sports analytics, or other real-time modeling applications
•	Experience with parallel computing, Rcpp, or lightweight scripting in Python
•	Experience scaling simulations using parallel file processing and efficient read/write workflows
•	Ability to recommend hardware scaling solutions (RAM, CPU, disk) when software optimization alone is insufficient

Engagement:

•	Part-time (20 hours/week) or full-time (40 hours/week)