We're looking for an experienced Portfolio Manager to build and scale systematic trading strategies across global agricultural markets.
This role is ideal for someone who combines deep knowledge of agricultural commodity fundamentals with a quantitative mindset. You'll have the opportunity to develop differentiated alpha by integrating supply and demand dynamics, weather, satellite imagery, logistics, positioning, and alternative datasets into systematic trading models.
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 or London, UK (onsite)
Key Responsibilities
Develop and manage systematic trading strategies across agricultural commodity markets.
Generate alpha by combining fundamental commodity research with quantitative modeling and statistical analysis.
Build predictive models using datasets such as weather, crop conditions, satellite imagery, freight flows, inventories, positioning, macroeconomic data, and other alternative data sources.
Design and evaluate new signals through rigorous research, backtesting, and performance attribution.
Continuously improve portfolio construction, risk allocation, and execution efficiency.
Partner closely with quantitative developers to productionize research and build scalable trading systems.
Work across the full research lifecycle, from idea generation through live deployment and ongoing monitoring.
Basic Requirements
Deep understanding of agricultural commodity markets, including supply and demand dynamics, seasonal effects, logistics, weather, and global trade flows.
Several years of experience managing or researching systematic 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.
Intellectual curiosity and a passion for developing new sources of alpha.
Nice to Have
Experience trading multiple commodity sectors beyond agriculture.
Familiarity with alternative datasets, remote sensing, satellite imagery, or geospatial analytics.
Experience with machine learning applied to 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
Skills Required
- Deep understanding of agricultural commodity markets including supply and demand dynamics, seasonal effects, logistics, weather, and global trade flows.
- Several years of experience managing or researching systematic 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.
- Intellectual curiosity and a passion for developing new sources of alpha.
- Experience trading multiple commodity sectors beyond agriculture.
- Familiarity with alternative datasets, remote sensing, satellite imagery, or geospatial analytics.
- Experience with machine learning applied to 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.
What We Do
Teza Technologies is an innovative quantitative asset management firm founded in 2009 by high-frequency trading expert Misha Malyshev. Our multi-strategy, multi-PM platform is founded on microstructure data and signals. Quantitatively-informed digital assets strategies complement our core global futures and stat arb strategies. We pride ourselves on attracting and retaining top talent, developing strategies with a data-driven and science-backed methodology, and continuously innovating in pursuit of alpha for our clients. Our 70 employees are distributed across offices in Austin, New York, Chicago, and Shanghai. phone: 312.768.1600 inquiries: [email protected] candidates: [email protected]
