The Role
Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.
Summary Generated by Built In
We’re building a new quantitative research team focused on pricing, market-making, and risk models for prediction markets. This is a highly hands-on role for someone who can operate end-to-end: data engineering, research, modeling, and close collaboration with traders, across sports and non-sports event markets and a range of contract types, including single-outcome markets, player props, and parlays.
Responsibilities:
- Build data foundation, transform raw data into pricing inputs
- Research and develop quantitative pricing, market-making, and risk models across sports, non-sports, player props, parlays, and correlated markets
- Model cross-market dependencies, correlations, and portfolio effects, especially for combinatorial products such as parlays
- Partner closely with traders to improve pricing logic, market coverage, and trading performance
- Build frameworks for backtesting, simulation, and model validation
- Create tools to monitor model performance, calibration, P&L attribution, and live trading outcomes
- Help define the tooling, workflow, and research standards for a new team
Requirements:
- Strong quantitative background in statistics, math, ML, economics, or a related field
- Experience building models in trading, sports, betting, prediction markets, or similar domains
- Strong Python/data skills and comfort owning data pipelines as well as modeling
- Ability to move quickly from raw data to research insight to production-ready mode
- High ownership, strong communication skills and comfortable with fast-paced high growth environment
Skills Required
- Strong quantitative background in statistics, math, ML, economics, or a related field
- Experience building models in trading, sports, betting, prediction markets, or similar domains
- Strong Python and data skills; comfortable owning data pipelines as well as modeling
- Ability to move quickly from raw data to research insight to production-ready mode
- High ownership, strong communication skills, and comfort with a fast-paced high growth environment
Crypto.com Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Crypto.com and has not been reviewed or approved by Crypto.com.
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Fair & Transparent Compensation — Pay is considered market‑competitive in select engineering, product, trading, compliance, and senior roles, with external postings and salary snapshots indicating strong bands in some geographies. Standout offers appear at higher levels, reinforcing that top‑of‑band packages are attainable in certain teams.
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Healthcare Strength — Benefit descriptions include medical, dental, and vision coverage across U.S. roles. Core health insurance is presented as part of a standard modern fintech package alongside other essentials.
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Leave & Time Off Breadth — Benefit materials reference PTO, sick time, and attractive annual leave with additional days for occasions. Time‑off provisions are positioned as a consistent element of the offering, with regional variation.
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The Company
What We Do
Crypto.com was founded in 2016 on a simple belief: it's a basic human right for everyone to control their money, data and identity. Crypto.com serves over 10 million customers today, with the world’s fastest growing crypto app, along with the Crypto.com Visa Card — the world’s most widely available crypto card, the Crypto.com Exchange and Crypto.com DeFi Wallet.
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