Triumph Logo

Triumph

Data Scientist

Reposted One Month Ago
In-Office
San Francisco, CA, USA
Mid level
In-Office
San Francisco, CA, USA
Mid level
As a Data Scientist at Triumph, you'll build models that optimize monetization, retention, and acquisition while analyzing user behavior data to drive strategic decisions.
The summary above was generated by AI
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.

Similar Jobs

Yesterday
Easy Apply
In-Office or Remote
2 Locations
Easy Apply
119K-173K Annually
Mid level
119K-173K Annually
Mid level
Healthtech • Information Technology • Mobile • Productivity • Software • Analytics • Telehealth
Commercial Data Scientist will develop machine learning models, analyze large healthcare datasets, identify clinician behavioral patterns, and create reusable data products. The role partners with Product, Data, Strategy, Insights, and Sales teams to deliver client-facing analyses and data-driven recommendations. Responsibilities include statistical analysis, production model development, complex SQL querying, scalable data processing, automation, and communicating technical insights through compelling visualizations and narratives.
Top Skills: Artificial IntelligenceDistributed Data ProcessingMachine LearningPythonPyTorchSQLTensorFlow
5 Days Ago
Easy Apply
Remote or Hybrid
USA
Easy Apply
200K-350K Annually
Senior level
200K-350K Annually
Senior level
Fintech • Software • Financial Services
Own the reliability and quality of an AI copilot for a trading platform. Build evaluation frameworks, benchmarks, quality gates, monitoring, incident response, and model improvement workflows. Partner with engineering and product to create safe, auditable tool interactions and improve assistant behavior. Develop domain expertise in trading, risk, margin, execution, and portfolio reasoning while operating across model, backend, and frontend systems.
Top Skills: Evaluation PipelinesLlm ApisModel ServingObservability And Telemetry ToolingPostgresReactReact NativeRustTraining PipelinesTypescript
5 Days Ago
Remote or Hybrid
7 Locations
95K-168K Annually
Entry level
95K-168K Annually
Entry level
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Develop data science solutions for payments across Square and Cash App. Build AI-powered tools, ETL pipelines, dashboards, machine learning models, experiments, and cloud data systems. Partner with Product, Engineering, Finance, and Operations to improve payment success, cost efficiency, risk mitigation, and decision-making. Translate business needs into practical solutions, research questions independently, and operationalize data processes and infrastructure.
Top Skills: AICloud InfrastructureETLMachine LearningPythonSQL

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account