Teza Technologies

Teza Technologies

Portfolio Manager, Systematic Agriculture

Austin

Sponsorship not specifiedDetected 22 days ago
PythonMachine LearningLogisticsResearchRemote Sensing

About the role

  • This role is ideal for someone who combines deep knowledge of agricultural commodity fundamentals with a quantitative mindset.
  • You'll work alongside experienced quantitative researchers, engineers, and data specialists while having the autonomy to shape research direction, portfolio construction, and execution.

Responsibilities

  • Develop and manage systematic trading strategies across agricultural commodity markets.
  • 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.
  • Partner closely with quantitative developers to productionize research and build scalable trading systems.
  • Experience building systematic investment strategies rather than discretionary trading alone.
  • Intellectual curiosity and a passion for developing new sources of alpha.

Requirements

  • Several years of experience managing or researching systematic commodity strategies.
  • Excellent Python programming skills and the ability to work with large datasets.
  • Strong understanding of portfolio construction, risk management, and systematic execution.

Nice to have

  • Experience trading multiple commodity sectors beyond agriculture.
  • 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
  • Strong quantitative background with experience applying statistical or machine learning techniques to financial markets.

This listing is sourced directly from Teza Technologies's careers page and normalized into a canonical job model.