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PGIM Fixed Income – Senior Quantitative Engineer
| Company | Prudential Financial |
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| Location | Newark, NJ, USA |
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| Salary | $170000 – $200000 |
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| Type | Full-Time |
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| Degrees | Bachelor’s, Master’s |
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| Experience Level | Senior, Expert or higher |
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Requirements
- Strong proficiency in programming languages such as Python, C++, or Java.
- Experience with quantitative libraries, APIs, and high-performance computing frameworks.
- Deep understanding of algorithms, data structures, and multi-threaded programming.
- Solid understanding of financial products, risk management, and portfolio construction.
- Familiarity with pricing models, market data, and risk systems.
- Proven experience leading development teams or mentoring developers.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
- 7+ years of professional experience in quantitative development, with at least 2 years in a leadership role.
Responsibilities
- Lead the end-to-end design, development, and implementation of quantitative models, libraries, and tools to support trading, portfolio management, and risk management.
- Provide architectural direction for systems ensuring scalability, performance, and maintainability.
- Advocate for best practices in software engineering, including code reviews, testing, and documentation.
- Build and optimize quantitative tools and frameworks using modern programming languages (e.g., Python, C++, Java).
- Collaborate with quants, traders, and portfolio managers to translate financial models and strategies into production-grade applications.
- Implement and enhance algorithms for data processing, analytics, and real-time decision-making.
- Work closely with cross-functional teams, including quant research, data science, and IT, to ensure seamless integration of systems.
- Mentor junior developers, fostering a culture of technical excellence and continuous learning.
- Manage the development lifecycle of critical projects, from requirements gathering through delivery.
- Communicate effectively with stakeholders, ensuring alignment on objectives, priorities, and timelines.
Preferred Qualifications
- Experience with cloud technologies (AWS, Azure) and containerization tools (Docker, Kubernetes).
- Knowledge of machine learning techniques and applications in finance.
- Familiarity with CI/CD pipelines and DevOps practices.
