crypto

Quant Trader (Sports & Prediction Markets)

🇺🇸 United States, Estados Unidos, Estados Unidos Presencial TI Lead Publicado Mai 29, 2026
Modalidade Presencial
Senioridade Lead
Categoria TI
Categoria IT Data Science e ML
Idioma English
Publicado 29 de Maio de 2026
Última verificação 29 de Maio de 2026

Onde esta vaga está disponível

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2 localizações
Estados Unidos
  • United States, Estados Unidos
  • Estados Unidos
Contexto da JobGrid

Resumo da vaga pela JobGrid

Quant Trader (Sports & Prediction Markets) at crypto is an on-site role in the United States, classified as IT / Data Science & ML at lead level. JobGrid normalizes the source facts, keeps the employer copy separate, and preserves the original application path.

  • Location and workplace: United States, on-site.
  • Comparable classification: IT, subcategory Data Science & ML.
  • Seniority level in the payload: Lead.
  • Source freshness: posted 2026-05-29 and last checked 2026-05-29; the source content is in English, and JobGrid keeps the original-language boundary intact while presenting a mapped
About the role: 

You will help design the engine powering OG.com’s liquidity. You’ll build and maintain a system for continuous, two-way quotes across thousands of simultaneous markets, bridging high-level theory and production-grade automation.
 
Focus: Architecting a multi-market autonomous pricing engine.

Responsibilities:

  • Autonomous Live Valuation: Engineer the logic synthesizing real-time sports data, player metrics, and market feeds into fair-value anchors and dynamic, real-time spreads.
  • Liability & Inventory Skewing: Build self-correcting models that automatically adjust odds based on book exposure and lopsided betting volume to incentivize balancing the book.
  • Defensive Design & Sharp Mitigation: Implement high-velocity protocols to mitigate adverse selection from "sharp" action, court-siding, and information asymmetry in milliseconds.
  • Risk Automation & Hedging: Define the algorithmic logic for warehousing sports risk internally versus routing and hedging exposure across external exchanges and market makers.
  • Technical Translation: Convert complex sports pricing strategies and mathematical models into scalable requirements for data and platform engineering teams.
  • Trading Desk Guardrails: Partner with the risk desk to define the engine’s operational boundaries, maximum liability thresholds, and automated kill-switches.
  • Real-Time Leadership: Act as the technical anchor during high-leverage sporting events, providing rapid calibration and manual intervention when the system is under peak pressure.

Requirements:

  • Quantitative Sports Fluency: Deep understanding of probability, binary prediction contracts, and sports analytics; treating every match, inning, or political event as a shifting probability curve.
  • Pipeline Design: Experience building production-ready betting or trading systems, from low-latency sports data ingestion (e.g., Opta, Sportradar) to automated bet acceptance engines.
  • Applied Data Science: Success deploying predictive models that learn from in-play microstructure, public betting sentiment, and price velocity.
  • Systems Integrity: Expertise in building error-tolerant infrastructure that remains rock-solid under extreme throughput (e.g., Super Bowl, World Cup, or election nights).