Trafigura

Trafigura

Quantitative Analyst, Gas & Power Trading

Houston, United States of America

Sponsorship not specifiedDetected 30 days ago
PythonC++C#Object-Oriented ProgrammingGitRedshiftExcelValuationCommunicationCollaborationMicrosoft Office

About the role

  • Reports into the Head of North America Quantitative Analysis, working closely with front office gas and power trading functions for North America.

Responsibilities

  • Developing and maintaining proprietary valuation library and internal pricing tools.
  • The North America Quantitative Analysis team at Trafigura provides modeling and pricing support for our North America trading and origination activities, with a primary focus on U.S. power and gas.

Requirements

  • Advanced degree in mathematics, physics, finance, engineering, or computer science.
  • In-depth knowledge and experience in financial mathematics, including option theory, derivative pricing, and risk analytics.
  • Proficiency in coding with programming languages such as Python, C#, C++, and/or VBA.
  • Working knowledge of database applications, including Amazon Redshift, Oracle, and Snowflake.
  • Familiarity with web-based applications such as Streamlit or DASH.
  • Knowledge and experience with ETRM/CTRM systems like Allegro or Endur.
  • Minimum of 3-5 years of experience in similar roles within commodity trading, preferably in U.S. power and gas.
  • Prior experience supporting trading and origination activities.
  • Working experience in building large-scale pricing model libraries in a team environment, utilizing software lifecycle collaboration tools such as GitLab or GitHub.
  • Development experience in object-oriented programming and design patterns.
  • Competency in MS Office applications.
  • Strong verbal and written communication, and good interpersonal skills.

Company info

  • We are seeking a highly motivated professional who aspires to excel in one of the leading global commodity trading organizations.

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