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Triumph

Quant Strategist

San Francisco, California, United States

Location
San Francisco, California, United States
Work
On-site
Employment
Full-time
Level
Not stated
Function
Data & AI
Pay
$200K – $400K a year
Posted
7 months ago

Pay and the market here

The top of this role’s range, $400K a year, is 54% above the median of $260K for data jobs in San Francisco (middle half $220K – $325K, 1,098 jobs that state pay).

1,323 data jobs open in San Francisco: 11% remote, 283 posted in the last 30 days.

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About the role

The Role

As a Quant Strategist, you'll sit at the intersection of mathematics, computer science, and core business decisions. You'll have a direct impact on all facets of the business, applying your quantitative rigor directly to what drives revenue and player experience. You'll build the models and frameworks that power our most critical business decisions.

You'd be joining a small, high-output quant team (4 people today) that operates more like a trading desk than a data org. We build the mathematical systems that power Triumph's core business: pricing engines, payout distributions, matchmaking algorithms, risk models, and player behavior systems.

The team is led by a former quant trader, and current members left careers in quantitative trading to be here. The problems are as deep and interesting as what you'd find at a quant fund - constrained optimization, adversarial dynamics, risk - but with more ownership, faster feedback loops, and direct impact on what gets built. You ship something, and you see it in the numbers the next day.

What You'll Do

  • Develop and optimize core risk-taking and revenue-generating algorithms — the pricing engines, payout structures, and edge calculations that are the mathematical backbone of Triumph's business.
  • Own the quantitative framework for Rips by Triumph: pricing models, pack economics, and rarity calibration.
  • Design and analyze experiments (A/B tests and beyond) with rigorous statistical methodology.
  • Identify high-leverage quantitative problems across the business and drive them from formulation to production impact.
  • Partner closely with engineering, product, and leadership to translate model outputs into real-time production systems and strategic decisions.
  • Design and build machine learning models that directly inform acquisition spend and product decisions.

Qualifications

  • Bachelor's degree in a quantitative subject: math, physics, computer science, data science, or a related discipline.
  • True depth and mastery over any quantitative domain: probability, statistics, applied machine learning, computer science, or math. We want spiky people who are confident that they are the best in their discipline.
  • Proficiency in Python and SQL.
  • Experience working with large amounts of data.

Preferred

  • Prior experience as a quantitative trader or quantitative researcher.
  • Experience in competitive math, physics, or CS olympiads, or a graduate degree in a quantitative discipline.
  • Nationally competitive in any activity. Some members from our company include national champions in debate, Clash Royale, and Poker.

Why Triumph?

  • High growth. Build a high-scale consumer platform that touches gaming, finance, and social with the autonomy to set our web direction.
  • High agency. Small, high-impact engineering team that is growing rapidly with significant opportunity for leadership and growth.
  • High energy. Passionate team who are proud of our work and velocity (16x year over year growth).
  • Competitive salary and benefits. $400/mo lunch credit, healthcare, vision, dental, 401k, etc.

Our team gathers 5 days a week at Triumph’s headquarters at Levi’s Plaza in San Francisco.

Source

Posted by Triumph on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 11:19 UTC; the original is the reference.

View the original ad ↗

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