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)