
Job Title: Quant Technology Engineer Commodities Risk (Python, Databricks & Derivatives Analytics) Location: Juno Beach (5 days Onsite)
Job Description:
Quant Technology Engineer Commodities Risk
Join a high performing Quant Technology team modernizing commodity risk platforms. You will migrate legacy SAS based risk models to Python, build scalable Databricks based frameworks, and develop distributed risk analytics supporting the risk team.
Responsibilities
Build and scale Python/PySpark risk models in Databricks (VaR, PFE, scenarios)
Develop high availability, distributed systems and microservices
Support valuation and risk analytics for commodity products (power, gas, oil)
Apply modern design patterns to continuously improve risk infrastructure
Write high quality, well documented production code
Requirements
Experience in front office or middle office development, preferably supporting commodity trading desks and derivatives risk analytics
Strong understanding of derivatives pricing, risk management, and market conventions
5+ years of hands on Python experience developing production grade risk models and analytics, with deep proficiency in Pandas, NumPy, and linear algebra based computations for numerical and time series analysis
Hands on experience scaling risk models in Databricks using PySpark for distributed risk calculations.
Experience with AI-assist coding tools
Solid understanding of distributed computing concepts, including data partitioning, parallel execution, and performance optimization.
Strong software engineering discipline across the full SDLC
Ability to quickly understand unfamiliar codebases and debug complex applications
Solid critical thinking and troubleshooting skills
What Will Make You Stand Out
Quant or Quant Dev experience in Commodities/Energy
Familiarity with modern data stacks
Strongly typed languages, CTRM systems, SAS experience.
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