Data Scientist

Volunteer Data Scientist – Statistical Analysis & Game Analytics
Organization: Nichual
Project: BilliArc
Position Type: Volunteer (Unpaid)
Work Arrangement: Remote, Flexible Schedule
Field: Data Science, Statistics, Game Analytics
About the Project
Developed at Nichual using vibe coding, BilliArc is a new variant of billiards played on a circular table with a single central pocket. Its unconventional geometry and gameplay offer interesting opportunities for statistical research, data analysis, and machine learning.
We are seeking Volunteer Data Scientists interested in investigating fundamental questions about game dynamics, competitive advantage, and player performance.
Research Objective
Does the player who starts the game have a statistically significant advantage?
The primary objective is to determine whether taking the first shot influences the final game outcome and whether this advantage varies depending on the relative skill levels of the two players.
Responsibilities
Collect experimental data from BilliArc's Watch Exhibition, where two AI agents compete at four different skill levels.
Organize datasets containing player skill levels, starting order, and final scores.
Apply appropriate statistical methods, including hypothesis testing, t-tests, and regression analysis.
Investigate the statistical significance and magnitude of any first-player advantage.
Visualize findings and prepare a concise research report.
Publish datasets, analysis code, and research findings on GitHub.
Qualifications
Background in statistics, mathematics, computer science, data science, or a related discipline.
Familiarity with statistical hypothesis testing, probability, and experimental design.
Experience with Python or R and common data analysis libraries.
Ability to interpret statistical results and communicate findings clearly.
Interest in game theory, billiards, or AI-based simulations is a plus.
Students, recent graduates, and early-career researchers are particularly encouraged to participate.
Dataset and Research Environment
All experimental data can be collected independently through the Watch Exhibition section of BilliArc.
The platform allows two AI agents to compete at four skill levels, enabling systematic analysis of different player combinations.
No registration, subscription, or payment is required.
What Volunteers Gain
This is an unpaid, independent research opportunity intended for individuals interested in developing practical data science skills and building a publicly accessible research portfolio.
Participants are strongly encouraged to publish their datasets, code, visualizations, and findings through their personal GitHub repositories.
These contributions can demonstrate practical experience in experimental design, statistical inference, and reproducible research, potentially supporting future academic or professional opportunities.
Get Involved
Interested candidates are encouraged to explore BilliArc, collect their own datasets, and develop independent approaches to the research question.
Explore BilliArc:
https://billiarc.ai.studio

Work arrangement
Yes