Date Posted: 2022-04-21

Job ID: EB-5294474340
Category: Commodities
Location: New York, NY

Quantitative Strategist – Commodities
Commoditites Fund
Location: New York (Hybrid / Flexible)


  • University degree with top grades
  • Minimum of a bachelor degree in computer science, computer engineering or like fields of study
  • Minimum 3 years of experience as a programmer/developer
  • Preferred: Minimum 3 years of professional experience within the IT Department of a trading and sales business in the Commodities Services Industry (Energy preferred)


  • Minimum 3 years of experience with Python. Any other modern OOP language will be considered.
  • Understanding of ETRM/CTRM Systems
  • Knowledge of US Energy markets specifically power and natural gas businesses
  • Experience with a beacon like system ideal (eg secdb/athena/quartz)
  • Experience with range of commodity modelling. Eg hourly scalars, load/gen forecasting, option pricing,


  • Languages: English
  • Communication skills to be able to act as a bridge between Traders, Orig, Mgmt and Quants.
  • Able to understand the needs of various functions such as Trading, Origination, Quant, Legal
  • Strong analytical skills for fast problem solving, innovative and solution focused


Discretionary Level

  • General Policies

Process/Project Responsibilities

  • Helping the business price and win new business with appropriate risk charges
  • Helping the business manage existing portfolios, especially complex books such as load, variable gen, FTRs.


  • Model creation/maintenance/refinement. Models such as:
    • Load/weather regression
    • Nodal/Zonal relationships
    • Nodal Loss modelling
    • Hourly Scalars
    • Load Migration
    • DA/RT pricing
  • Assist trading team in managing portfolio
  • Creating tools to facilitate deal pricing and risk management processes
  • Maintenance of quant code base
  • Building/enhancing tradable instruments to accommodate new deal types/parameters
  • Option pricing
  • Development of tools to summarize position and risks for traders and management

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