About the job
About Triumph Arcade
At Triumph Arcade, we are revolutionizing mobile gaming by allowing players to wager real money, participate in thrilling multiplayer competitions, and engage in social tournaments. Our innovative app has quickly become a top performer in its category on the App Store, experiencing remarkable month-over-month growth in both revenue and active users. As we continue to expand our offerings, including successful new products like Rips, we are on a mission to redefine the gaming experience.
Supported by leading venture capital firms such as Goodwater Capital, General Catalyst, and DraftKings Drive Fund, Triumph Arcade is positioned for explosive growth.
The Role
As a Quantitative Strategist, you will occupy a pivotal role that merges mathematics, computer science, and strategic business insights. Your analytical prowess will directly influence our revenue streams and enhance player experiences as you craft the models and frameworks that underpin key business decisions.
Joining our compact but impactful quant team (currently 4 members), you will find an environment akin to a trading desk rather than a conventional data organization. We are responsible for the mathematical systems that drive Triumph's core operations, developing pricing engines, payout mechanics, matchmaking algorithms, risk assessments, and player behavior models.
Led by a former quant trader, our team consists of professionals who have transitioned from quantitative trading to tackle equally complex problems with a greater sense of ownership and quicker feedback loops. You will have the opportunity to implement solutions and witness their impact on performance metrics almost immediately.
Key Responsibilities
- Design and refine algorithms that drive our risk-taking and revenue-generating strategies, including pricing engines and payout frameworks.
- Oversee the quantitative strategy for Rips by Triumph, including pricing models and rarity calibrations.
- Conduct and evaluate experiments (A/B tests and beyond) using robust statistical methods.
- Identify and tackle high-impact quantitative challenges throughout the organization, guiding them from conception to execution.
