
Quantitative Developer – Python
at Millennium
Posted 4 hours ago
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Join Millennium's Risk Technology team to design and build Python-based data pipelines, analytics libraries, and dashboards for risk and portfolio managers. The role involves prototyping and delivering cloud-native (AWS) data-intensive applications, evolving risk system architecture, and collaborating closely with risk management to improve risk metrics and visualizations.
Millennium is a top tier global hedge fund with a strong commitment to leveraging innovations in technology and data science to solve complex problems for the business.
Risk Technology team is looking for a Quantitative Developer who would leverage Python, Cloud infrastructure (AWS), and scientific frameworks to provide data-driven risk management solutions and dashboards to Risk Managers, & Business Management.
Responsibilities:
Design, develop, and maintain data pipelines, dashboards and analytics library.
Collaborate with risk management for rapid prototyping and delivery of solutions to enhancement risk metrics and data visualization.
Design and implement cloud-native, data-intensive applications that effectively leverage AWS solutions
Fit into the active culture of Millennium, judged by the ability to deliver timely solutions to Portfolio and Risk Managers
Participate in evolving overall infrastructure and architecture/design for risk systems with technology trends, tools and best practices.
Requirements:
Minimum 2 years of experience using Python to build piplelines/dashboards using python libraries (e.g., pandas, NumpPy, SciPy, Plotly).
Strong understanding of cloud infrastructure and experience working with cloud services (e.g., AWS, Azure).
Prior experience in system design and data modelling, with the ability to architect scalable and efficient solutions for trading, risk management or similar functions.
Strong analytical and mathematical skills, with interest and exposure to quantitative finance and financial products
Relational database development experience, with a focus on designing efficient schemas and optimizing queries.
Unix/Linux command-line experience.
Ability to work independently in a fast-paced environment.
Detail-oriented, organized, demonstrating thoroughness and strong ownership of work.

