Benjamin Cabalona
Benjamin is a Data Science Manager by day and a passionate Homelab enthusiast by night. Outside of his professional and technical pursuits, he takes pride in being a dad, staying active as a gym enthusiast, and maintaining a sharp appearance.
In addition to his work-life balance, Benjamin spearheaded a community project aimed at addressing the 'you need experience to get experience' dilemma faced by many aspiring professionals. Details of this initiative can be found on his blog: https://blog.cauchy.dad.
Session
This talk focuses on the use of Python in building and implementing simulations tailored for the casino environment. Sample use cases:
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Game Mechanics Optimization: Leveraging Monte Carlo simulations and custom probability models to test and refine the payout structures and mechanics of games, ensuring regulatory compliance and an engaging player experience.
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Risk Analysis: Applying simulation techniques to evaluate operational risks, such as managing jackpot payouts and assessing the financial impact of rare but high-stakes events.
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Scenario Testing: Using Python to model and stress-test hypothetical situations, such as changes in customer behaviors, or adjustments in game rules, providing valuable insights for strategic planning.