VP, Quantitative Development
VP, Quantitative Development
Selby Jennings has partned with the Asset Management arm of a global financial insitution. Our client is scaling several Quant teams to kick off new projects, initiatives, and platofrms.
Responsibilities:
- Lead the architecture and development of robust, scalable systems for investment risk and portfolio analytics, with a focus on multi-asset class risk modeling, performance attribution, and optimization.
- Lead, mentor, and build a team of talented quant developers, fostering a collaborative, high-performance environment. Provide technical leadership and guidance in all stages of the software development lifecycle.
- Provide technical leadership in building scalable, high-performance systems that handle large volumes of data, ensuring the systems can support complex risk models at scale.
- Lead the adoption of modern software engineering practices, including CI/CD, containerization (Docker), serverless architectures, and cloud technologies to enhance development and operational efficiency.
- Work with business partners to design and implement sophisticated quantitative risk and portfolio analytics systems that support decision-making processes in asset management.
Qualifications:
- 10+ years of experience in software development, quantitative development, or financial technology, with a strong focus on investment risk systems in buy-side asset management firms.
- Strong knowledge of risk modeling, including factor-based risk models, scenario analysis, stress testing, and factor attribution.
- Proficiency in Python (especially libraries like Pandas, NumPy, Dash) for building data-driven applications.
- Familiarity with C++ for performance-critical systems.
- Experience with containerization (Docker), serverless computing, and API management.
- Familiarity with front-end technologies like HTML5, JavaScript, CSS3, and Angular.
- Experience with CI/CD pipelines, infrastructure-as-code, and test-driven development.
- Proficiency with data pipeline engineering, ETL processes, and working with big data technologies for processing large datasets efficiently.
- Strong experience with performance at scale, parallel computing, and high-performance computing.
- Proficient in system architecture and design
- Proven ability to lead and mentor teams of quantitative developers, fostering an environment of collaboration, innovation, and continuous improvement in risk and software development practices.
- Executive Communication - Ability to communicate based on the partners from concise information to precise details based on the audience.
- Bachelor's or higher degree in Computer Science, Applied Mathematics, Financial Engineering, or a related quantitative field.
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