
Software Engineer - Risk Technology
at Millennium
Posted 19 hours ago
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Full Stack Engineer specializing in Angular and Python to support enterprise risk technology for the CIO team. The role involves building web applications using Angular and FastAPI, implementing asynchronous workflows, and developing Python tools for quantitative analysis. You will collaborate closely with quant teams and internal data providers, create reusable code packages, and automate tasks to ensure timely, high-quality data delivery. The position requires independent problem-solving, attention to detail, and the ability to work in a fast-paced, global team environment.
- Design, develop, and maintain web applications using Angular and FastAPI.
- Implement asynchronous programming workflows to enhance application performance and scalability.
- Develop Python applications and tools for quantitative analysis and modeling.
- Build functional Angular components using Typescript and NextJS.
- Collaborate with quant teams to understand and implement their requirements.
- Identify and create reusable code packages.
- Document development phases and monitor systems.
- Automate tasks through appropriate tools and scripting.
- Collaborate with internal teams and upstream internal data providers.
- Stay up to date with industry trends, emerging technologies, and best practices.
- 3+ years of professional software engineering or development experience.
- 3+ years of professional experience with Angular, or other typescript frameworks will also be considered.
- Bachelor's degree in Computer Science or related field.
- Strong understanding of synchronous and asynchronous programming and their applications.
- Strong understanding of data structures, data modeling, and software architecture.
- Excellent analytical and problem-solving skills.
- Proficient in both written and verbal English communication.
- Ability to work independently and as part of a global team.
- Knowledge in Math and statistics.
- Familiarity with data engineering libraries such as Polars, Pandas, Numpy, etc.
- Experience working with large datasets and time series data.
- Experience working with AWS (especially EC2, S3 and Redshift).
- Knowledge in finance.
- Prior experience in quantitative development.





