### About Synth
Synth is a frontier financial research company and trading firm.
Synth is powered by an open, adversarial machine learning competition where
independent researchers and models generate future price distributions across
financial markets. These forecasts are evaluated continuously and applied to
our live trading and market-making systems.
Our goal is to build the most advanced synthetic state-price engine in
finance: a system that can model not just where markets may go, but the full
probability distribution of future outcomes.
We are looking for a Quant Trader to help turn Synth’s probabilistic forecasts
into live trading strategies across prediction markets, options, and perpetual
futures markets.
### The role
You will be responsible for designing, running, and improving trading
strategies using Synth’s forecast data as a core input.
This is a hands-on trading role. You should have experience deploying
profitable strategies in production, managing risk in live markets, and
iterating quickly based on market feedback.
You will work closely with our research and engineering teams to translate
probability distributions, volatility forecasts, and market microstructure
signals into executable strategies across crypto-native and traditional market
structures.
### Responsibilities
* Manage trading strategies across options, prediction markets, and perpetual futures.
* Use probabilistic forecasts to inform pricing, skew, volatility, inventory management, and risk limits.
* Work with engineers to improve trading infrastructure, execution systems, monitoring, and risk controls.
* Collaborate with ML researchers to translate model outputs into practical trading signals.
* Develop frameworks for evaluating when forecasts create a measurable trading edge.
* Help expand trading coverage across new assets, venues, and market types.
### Requirements
* 2–3+ years running trading strategies in live markets.
* Strong understanding of market making, execution, hedging, and risk management.
* Ability to reason from distributions, volatility forecasts, and market-implied pricing.
* Strong Python skills for research, backtesting, data analysis, and strategy development.
* Clear understanding of PnL attribution, inventory risk, adverse selection, and liquidity provision.
* High ownership mindset and the ability to operate independently in fast-moving markets.
### What you'll work on
* Market-making systems for event contracts.
* Options strategies using volatility models.
* Cross-market hedging between perps, options, spot, and prediction markets.
* Live trading systems that convert forecasts into executable edge.
* Risk models for inventory, liquidity, volatility, and tail events.
### Who you are
You care about execution, risk, and live PnL. You are comfortable operating in
imperfect markets where liquidity is fragmented, data is noisy, and edge has
to be discovered through iteration.
You are excited by the idea of combining frontier machine learning research
with live trading systems, and you want to help build one of the first trading
firms powered by a synthetic state-price engine.
### How to Apply
Send your CV and a cover letter explaining your relevant trading experience.
Bonus points if you include examples of strategies you have run, markets you
have traded, and how you think Synth’s probabilistic forecasts could be
applied to market making.