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Data Scientist

Triumph triumpharcade.com Open · verified Oct 24, 2026
On-site San Francisco Full-time Mid-level Data Science

At a glance

Mid-level Data Science role at Triumph. San Francisco · full-time · $200,000–$400,000 base.

SalaryStated by Triumph
$200,000 – $400,000
Base salary for this role, in USD per year, as published in the posting.
This role, from TriumphOur estimate for the market: $172,375–$223,788Median $207,750
The range includes the market median of $207,750 for mid-level data science roles in San Francisco.
Worked out from 32 postings that stated pay, median $207,750. Last updated Oct 24, 2026.
RoleData Science
SeniorityMid-level
LocationSan Francisco
WorkplaceOn-site
EmploymentFull-time
Base pay$200,000–$400,000
PostedApr 1, 2026 · 6mo ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build and tune pricing, payout, and edge models, including pack economics and rarity settings for Rips by Triumph
  • Map player behavior from acquisition through churn, then test interventions to improve retention and lifetime value
  • Design product experiments and set the statistical measures used to judge whether changes work
  • Use session, spending, matchmaking, and gameplay data to build models for product choices and live systems
  • Connect acquisition spend and channel choices to downstream player value, then work with engineering and product to ship findings

What you bring

  • A bachelor’s degree in a quantitative discipline such as math, physics, computer science or another listed field
  • Deep command of at least one area such as probability, statistics, applied machine learning, causal inference or mathematics
  • Proficiency in Python and SQL, plus experience analyzing large user or behavioral datasets

Who this fits

You’ll suit a hands-on quantitative role spanning pricing, player behavior, experimentation and growth models. The position is based on-site in San Francisco, with the team gathering at its headquarters five days a week.

From the employer

The Role

As a Data Scientist, you'll own the quantitative systems that drive how millions of players experience Triumph's products, from their first session to long-term retention and monetization. You'll build the models and frameworks behind our most critical business decisions: how we price, how we pay out, how we match players, and how we grow.

You'd be joining a small, high-output quant team (4 people today) that operates like a trading desk. We build the mathematical systems that power Triumph's core business: pricing engines, payout distributions, matchmaking algorithms, risk models, and player behavior systems. Every model we ship touches money and real users. You see the impact in the numbers the next day.

What You'll Do

  • Monetization & Pricing: Develop and optimize the pricing engines, payout structures, and edge calculations that are the mathematical backbone of Triumph's revenue. Own pack economics, rarity calibration, and pricing models for Rips by Triumph.

  • User Journey & Retention: Build models that map the full player lifecycle: acquisition, activation, engagement, monetization, churn risk. Identify the quantitative levers that move retention and LTV, and design interventions that act on them.

  • Experimentation: Design and analyze experiments (A/B tests and beyond) with rigorous statistical methodology. Own the measurement framework that tells us what's actually working across the product.

  • Behavioral Modeling: Develop ML and statistical models on rich, high-frequency user behavior data (session patterns, spend curves, matchmaking outcomes, gameplay trajectories) to drive both product decisions and real-time production systems.

  • Growth & Acquisition: Build models that directly inform acquisition spend and channel optimization, connecting upstream marketing decisions to downstream LTV and monetization outcomes.

  • Cross-Functional Impact: Partner closely with engineering, product, and leadership to translate model outputs into shipped features and strategic decisions. Identify high-leverage quantitative problems across the business and drive them from formulation to production impact.

Qualifications

  • Bachelor's degree in a quantitative subject: math, physics, computer science, statistics, economics, or a related discipline.

  • True depth and mastery in at least one quantitative domain: probability, statistics, applied ML, causal inference, or mathematics. We want spiky people who are confident they are among the best in their discipline.

  • Proficiency in Python and SQL.

  • Experience working with large-scale user or behavioral datasets.

Preferred Qualifications

  • Experience in consumer tech, gaming, fintech, or marketplace data science, particularly in monetization, LTV modeling, or experimentation.

  • 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 of our team 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.

Opportunity

Data Science work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Science$200k+

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Science work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.