Job Description

Salary: $36,000 - 36,000 per year Requirements:

• Strong Counter-Strike knowledge and genuine game understanding, since feature design depends on it
• Solid Python fundamentals, as part of the interview will be completed without assistance
• Current study in, or completed study of, data science, computer science, statistics, machine learning, or a related field
• Familiarity with XGBoost or comparable models is helpful, though not mandatory
• Experience with SHAP or similar attribution techniques is an advantage, but not required
• Any background in sports or esports analytics would be beneficial
• We welcome non-traditional career paths and candidates making a career transition

• Explore our tick-level data to uncover useful patterns and signals
• Engineer features for a round win probability model using match-state information such as economy, positioning, player count, equipment, bomb status, and time
• Train, test, and validate a state-of-the-art model to predict each sides chances of winning a round
• Design an explanation layer that shows which factors influence each prediction and by how much
• Balance predictive performance with interpretability and present a clear rationale for the approach chosen
• Document your findings and write up the results of the project
• Build work that is intended to ship to production

• Machine Learning
• Python

More:

We are PureSkill.gg, an automated coaching platform for Counter-Strike 2 that analyzes players match demos and generates personalized feedback without human intervention. This is a remote project with a flexible start, available full-time or part-time with no hour tracking, and it offers a flat stipend of $3,000 USD per month. The engagement is expected to run for about 4 weeks, and we are looking for someone who can help us build a production-ready, explainable round win probability model for coaching use.

last updated 30 week of 2026

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