Quant Technology Engineer – Commodities Risk
Location:
Juno Beach, FL
Rate:$36–41/hr
Duration:
8-month contract
Schedule:
Standard business hours
Overview
Join a high-performing Quant Technology team within a leading organization in the energy sector. This role focuses on modernizing commodity risk platforms by migrating legacy SAS-based models to Python, building scalable Databricks frameworks, and developing distributed risk analytics to support front-office risk functions.
Key Responsibilities
- Develop and scale Python/PySpark-based risk models in Databricks (e.g., VaR, PFE, scenario analysis)
- Design and implement high-availability distributed systems and microservices
- Support valuation and risk analytics for commodity products (power, gas, oil)
- Apply modern software design patterns to enhance and optimize risk infrastructure
- Write high-quality, maintainable, and well-documented production code
Required Experience & Skills
- Experience in front-office or middle-office development, ideally 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
- Advanced proficiency in Pandas, NumPy, and linear algebra for numerical and time-series analysis
- Hands-on experience using Databricks and PySpark for distributed risk computations
- Familiarity with AI-assisted coding tools
- Strong understanding of distributed computing concepts (data partitioning, parallel processing, performance optimization)
- Solid software engineering practices across the full SDLC
- Ability to quickly understand and debug complex codebases
- Strong analytical thinking and problem-solving skills
Preferred Qualifications
- Experience as a Quant or Quant Developer within commodities or energy trading
- Familiarity with modern data platforms and architectures
- Experience with strongly typed languages
- Exposure to CTRM systems and/or SAS
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