Quantitative Software Engineer (Quantitative Investment)

Job Title: Quantitative Software Engineer (Quantitative Investment)

Job Location: Morristown, NJ

Work Model: Hybrid (Onsite 3x/week)

Job Type: Permanent / Full-Time

Mode of Interview: Video / Technical Interview (Onsite Final)

Must Have Skills: Strong Python/Julia, C/C++, Data Repository Architecture (SQL/Oracle), Math/Statistics aptitude, MS/PhD degree

Position Summary:

This position plays a key role in contributing to core quantitative investment processes. Quantitative Software Engineers are responsible for the design, implementation, optimization, and testing of proprietary quantitative investment systems. Working as part of a collaborative team, the role involves building high-performance systems, managing data infrastructure, and enhancing portfolio models.

Key Responsibilities:

• Quantitative Modeling & Optimization: Implement and enhance quantitative models, proprietary portfolio construction, and optimization techniques in close collaboration with Research and Portfolio Management teams.
• Data Architecture: Architect and manage global data repositories incorporating millions of financial and market data points.
• High-Performance Computing: Create high-performance simulation and optimization engines.
• Workflow Systems: Develop and manage end-to-end investment workflow management systems.
• Analytics & Reporting: Build and extend analytics and reporting platforms.

Requirements & Qualifications:

Education:

• MS or PhD degree in Computer Science, Engineering, Statistics, or a related quantitative discipline.

Core Programming:

• Strong programming proficiency in Python or Julia (experience with NumPy/Pandas or similar quantitative software is a plus).
• Hands-on programming experience in C/C++ .

Database Management:

• 2+ years of experience with relational database technologies (e.g., SQL Server, Oracle).

Technical & Analytical Aptitude:

• Outstanding coding, debugging, and analytical skills paired with a strong aptitude for mathematics and statistics.

Problem Solving:

• Passionate about solving complex business, data, and technical challenges.

Knowledge of .NET and C# .

Active contributions to open-source software.