Trading Analyst – QPT (Quantitative Positional Trading)
An analyst role in Maven's growing QPT options team, researching strategies, maintaining desk infrastructure and attributing performance. It combines research with running production trading systems.
What you’d work on
Our reading of the posting: what a new hire in this role would most likely spend their first months on.
- Backtest alphas across the volatility surface, term structure and dispersion
- Run PnL attribution and track volatility surface changes
- Prototype and iterate on ideas with traders
- Keep desk trading systems stable around the clock
- Build dashboards for discretionary traders
What they ask for
Required
- Strong Python
- Strong SQL
- Clear communication in a fast environment
- Interest in financial markets and derivatives
Preferred
- Quant development or research experience
- Portfolio construction
- Docker, Kubernetes, ArgoCD
- Production systems experience
- C++, C# or TypeScript
- AI tools
- Education
- Not stated
- Experience
- Early-career; derivatives desk or quant development background preferred
- Languages and tools
- Markets
- options
How to prepare
- Backtest a volatility term-structure signal and attribute its PnL
- Learn Docker basics and deploy a small scheduled data job
- Build an options analytics dashboard
- Study 0DTE options and dispersion trades
What to study
- Python for Quantitative Finance
- Derivatives Pricing and Computational Finance
- Quantitative Research, Data and Backtesting
- Quantitative Data Engineering
The Volatility Quant roadmap sets out the stages for this kind of role, with free resources for each.
Open the roadmapApply
Read the full posting on Maven Securities’s site before applying: requirements, location and pay can change after we check them.
View the posting on Maven Securities’s site ↗
SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Maven Securities and doesn’t handle applications.