Systematic Portfolio Manager, Energy

We're looking for an experienced Portfolio Manager to build and scale systematic trading strategies across global energy markets.

This role is ideal for someone who combines strong knowledge of energy markets with a quantitative mindset. You'll develop trading strategies using fundamental market data, weather, supply and demand dynamics, physical flows, positioning, and other datasets.

You'll work alongside experienced quantitative researchers, engineers, and data specialists while having the autonomy to shape research direction, portfolio construction, and execution.

Location
Austin, TX (onsite) or London, UK (onsite)

What you’ll do

- Develop and manage systematic trading strategies across global energy markets.
- Generate trading signals by combining fundamental energy market research with quantitative modeling and statistical analysis.
- Build predictive models using various datasets ranging from technical (price/volume) to alternative data sources.
- Design and evaluate new signals.
- Improve portfolio construction, risk allocation, and execution.
- Work across the full research lifecycle, from idea generation through live deployment and ongoing monitoring.

What we’re looking for

- Experience across multiple energy markets, including power, natural gas, crude oil, or refined products.
- Deep understanding of energy markets, including supply and demand modelling, seasonality, storage, logistics, and physical market flows.
- Several years of experience managing or researching systematic energy or commodity strategies.
- Strong quantitative background with experience applying statistical or machine learning techniques to financial markets.
- Excellent Python programming skills and the ability to work with large datasets.
- Experience building systematic investment strategies rather than discretionary trading alone.
- Strong understanding of portfolio construction, risk management, and systematic execution.
- Strong interest in energy markets and quantitative research.

Nice to Have Requirements

- Experience with machine learning applied to energy or commodity forecasting.
- Knowledge of real-time research infrastructure and production trading systems.
- Graduate degree in a quantitative discipline.
- Track record of managing external or proprietary capital.

Benefits

- Health, visual and dental insurance
- Flexible sick time policy