Executive Director (Senior Lead Securities Python Quantitative Developer )
On-siteCharlotte, North Carolina, United States
Job Summary
Implement ALM models and logic in Python, integrating pricing and risk analytics with other quant teams to enhance the Juniper Vasara risk platform. Analyze performance metrics, propose optimization plans, and ensure execution of strategic valuation and risk solutions for portfolio management partners. Collaborate with business stakeholders, technology partners, and project managers to resolve design issues, balance project objectives, and deliver high-quality software within an Agile SDLC. Proactively participate in complex software design and generate testable ideas to improve system performance and team productivity while adhering to strict compliance and risk mitigation protocols.
Required Qualifications
- 7+ years of Securities Quantitative Analytics experience
- 7+ years of professional Python 3 experience
- Must be able to work on-site
- Ability to travel up to 10% of the time
- Must be able to work on-site
- This position is eligible for Visa sponsorship
Desired Qualifications
- 5+ years of hands-on coding experience
- Python and C++ are most relevant
- 3+ years of product and market experience in various asset classes: rates, foreign exchange, credit, and mortgages, and structured products
- 3+ years of quantitative analytics library software development experience in a buy-side or sell-side institution or a quant solution vendor
- 1+ year hands on experience with ALM frameworks or prior experience in ALM vendor software
- Strong proficiency in Python is encouraged
- Understanding of advanced language features, runtime behavior, and performance characteristics
- Deep understanding of CPython internals (interpreter loop, memory model, GIL, garbage collection)
- Experience customizing or extending the Python interpreter or standard library
- Proven experience with Python interoperability and bindings to lower-level languages (e.g., C/C++, Cython, pybind11, Java)
- Hands-on experience writing high-performance GPU code using Python-based DSLs (e.g., Triton, CUDA Python, JAX/XLA kernels)
- Demonstrated expertise in Python performance optimization across CPU architectures using tools such as Numba, Cython, vectorization, and profiling techniques
- Experience designing and developing large-scale, distributed, high-performance Python systems in production
- Strong understanding of multithreading and multiprocessing in Python, including practical strategies for working with or around the GIL in real-world production environments
- Experience operating Python systems under strict latency, throughput, or reliability constraints (e.g., low-latency trading systems, ML inference serving, large-scale data pipelines)
- Experience interpreting and solutioning for risk
- Master's degree or higher in computer science or finance/mathematics
- Experience in software development cycle and agile technologies, e.g., Git, Jira, Confluence
- Experience in or passionate about Agentic AI
- Excellent verbal, written, and interpersonal communication skills
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