About the role
What we're looking for:
We need someone with 2–8 years of experience in quantitative trading, research, or applied probability who has deep mastery in probability, game theory, and statistics. You should be comfortable operating with high autonomy on a small, elite team and have a track record of solving complex mathematical problems with direct business impact. Bonus points if you can contribute to backend engineering and have experience with consumer-facing products.
What you'll do:
- Develop and optimize core risk-taking and revenue-generating algorithms — pricing engines, payout structures, edge calculations, and pack economics that are the mathematical backbone of Triumph's business
- Own the quantitative framework for products like Rips by Triumph: pricing models, rarity calibration, and constrained optimization problems comparable in depth to quant trading
- Design experiments (A/B tests and beyond) with rigorous statistical methodology to tune game mechanics and maximize revenue while preserving player experience
- Identify high-leverage quantitative problems across the business and drive them from mathematical formulation to production impact — you ship something and see it in the numbers the next day
- Partner closely with engineering, product, and leadership to translate model outputs into real-time production systems and strategic decisions
- Build machine learning models that directly inform acquisition spend, player behavior prediction, and product decisions
- Contribute to backend engineering and codebase when possible — this is a strong nice-to-have and more emphasized here than on the Data Scientist role