What are the responsibilities and job description for the Quantitative Software Engineer (Quantitative Investment) position at Amtex Systems Inc?
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.