Quantitative Research Energy Analyst @ JPMorganChase
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Introduction
Join our dynamic team as a Quantitative Research Energy Analyst at JPMorganChase. You will play a pivotal role in shaping the future of our market-leading Whole Loan and Securities trading business.
Job Description
As an Analyst within the Quantitative Research team, you will collaborate directly with top traders to create tools and analyses that revolutionize trading operations. You will work alongside a dedicated, skilled team that values integrity, hard work, and creativity. A strong foundation in computer science, mathematics, or finance with excellent programming skills in Python is essential.
Job Responsibilities
- Manipulate large datasets to produce systematic analyses and reports.
- Develop Python scripts and tools for market and trading analysis.
- Collaborate with technology teams on trading and P&L systems.
- Build tools to streamline trading operations and improve efficiencies.
- Assist in the development of internal pricing and risk models.
Required Qualifications
- Strong academic background in computer science, mathematics, or finance.
- Excellent programming skills in Python.
- Excellent communication and analytical skills.
- Solid understanding of mathematical and financial market concepts.
- Self-motivated with strong critical and independent thinking abilities.
Preferred Qualifications
- Knowledge of SQL.
- Prior financial experience.
- Mortgage industry knowledge.
About JPMorganChase
JPMorganChase is one of the oldest financial institutions, offering innovative solutions to millions across diverse sectors. With over 200 years of history, JPMorganChase leads in investment banking, consumer banking, commercial banking, financial transaction processing, and asset management.
Key skills/competency
- Python
- Data Analysis
- Trading
- Risk
- Pricing
- SQL
- Financial Markets
- Mathematics
- Research
- Tool Development
How to Get Hired at JPMorganChase
🎯 Tips for Getting Hired
- Research JPMorganChase's culture: Study their mission, values, and recent news.
- Customize your resume: Highlight Python and financial analysis skills.
- Network on LinkedIn: Connect with current employees for insights.
- Prepare for technical questions: Review data and risk modeling theories.