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Fidelity Bank · 12 hours ago

Quantitative Risk Developer

Jersey City, NJ

Full-time

Hybrid

Senior Level

$100K/yr - $200K/yr

5+ years exp

Fidelity Bank is seeking a highly motivated and experienced Quantitative Risk Developer to join their Quantitative Research and Investments team. The role involves building Fidelity's next-generation portfolio analytics platform and collaborating with quantitative researchers and technologists to enhance risk management capabilities.

BankingBitcoinCustomer ServiceFinancial ServicesInsuranceWealth Management

Responsibilities

Design, develop, and implement core risk capabilities for Fidelity’s risk management platform, focusing on:

Multi-asset class ex-ante risk modeling

Performance attribution analysis

Stress testing and scenario analysis

Collaborate with quantitative risk managers to build cutting-edge tools and software libraries, advancing our analytical capabilities

Apply software development best practices to optimize run-time performance, scalability, and robustness of the platform

Partner with technologists to ensure seamless integration of quant codebase with existing systems, data infrastructure, and production environments

Engage with investment professionals across Fidelity Asset Management to understand their evolving needs and ensure the risk platform meets their business requirements

Qualification

Python programmingQuantitative modelingRisk managementSoftware version controlAI/ML fundamentalsInteractive Python GUIsCommunication skills

Required

Master's degree with an outstanding academic record in a technical field such as science, engineering, or mathematics, with 5+ years of experience as a quant developer for an investment firm. Bachelor's degree with 7+ years of relevant experience may be considered

Expert Python programming skills with a strong emphasis on libraries used in quantitative finance, including NumPy and SciPy

Good understanding of software version control with strong Git proficiency, testing methodologies, code reviews, documentation, and other best practices

Understanding of AI/ML fundamentals; familiarity with tools like GitHub Copilot; experience applying AI techniques for time series data anomaly detection

Strong communication skills with the ability to effectively convey complex technical information to both technical and non-technical audiences