Senior Quantitative Analyst

23 hours ago


Omaha, Nebraska, United States The Scoular Company Full time
About the Role

The Senior Quantitative Analyst will be responsible for conducting market research and modeling to support the Senior Traders/Merchants on the derivative risk desk. This role will be responsible for supporting the team's trading activities, quantitative model building, ensuring smooth and efficient execution of trades and maintaining accurate records and reporting.

This role will work closely with the portfolio management, trading and compliance teams to optimize trading workflows and mitigate operational risks. The Senior Quantitative Analyst will collect, analyze and present data on portfolio risk and performance using Python and other analytical tools.

Key Responsibilities:
  • Conduct market analysis to identify trading opportunities and assess risks requiring a deep understanding of market concepts and a thorough knowledge of a product or financial area, including market liquidity and volatility, pricing, trading and hedging strategies and marketing and origination.
  • Collect and organize data on portfolio positions, trades and market data that will be used for performance metrics such as returns, volatility, drawdowns and risk adjusted returns
  • Develop and maintain Python scripts and notebooks for data processing and analysis
  • Help build and maintain processes to manage the daily trade lifecycle, including order entry, allocation, confirmation and settlement
  • Assist with the implementation and testing of new trading systems and tools
Requirements:
  • Bachelor's degree in finance, accounting, statistics or related field.
  • Minimum of 7 years work related experience.
  • Knowledge of commodity markets, instruments and quantitative investment strategies
  • Excellent communication and interpersonal skills with the ability work effectively with cross-functional teams.
  • Highly organized, detail oriented and able to multitask in a fast paced environment.
  • Proficiency in SQL, Python and relational databases for data extraction and manipulation.
  • Familiarity with risk management concepts
Preferred:
  • Strong programming skills in Python and experience with data analysis libraries like NumPy and Pandas


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