Quantitative Software Engineer (Quantitative Investment)

Job Title: Quantitative Software Engineer (Quantitative Investment)Job Location: Morristown, NJWork Model: Hybrid (Onsite 3x/week)Job Type: Permanent / Full-TimeMode 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 degreePosition 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.