Role Summary
The Quant Development team collaborates with the Advanced Strategies and Research group within Asset Management. The team focuses on developing innovative solutions for systematic investment strategies, portfolio construction, risk management, and alpha research. They are at the forefront of integrating generative AI technologies to enhance decision-making and operational efficiency in asset management.
Key Responsibilities
- Leadership and Development:
- Lead and mentor a team of engineers, fostering growth and development.
- Oversee the design and implementation of scalable systems, focusing on distributed systems, microservices, event-driven architectures, and data pipelines.
- Technical Expertise:
- Leverage deep expertise in Python and full-stack development to build robust solutions.
- Utilize object-oriented programming and design patterns effectively.
- Implement unit testing frameworks and advocate for test-driven development (TDD) practices.
- Work with a variety of database technologies, including SQL (Oracle, Snowflake), NoSQL, Graph, and Vector databases.
- Cloud and DevOps:
- Utilize AWS infrastructure with infrastructure-as-code tools like CloudFormation.
- Implement CI/CD pipelines and adopt best practices in DevOps.
- Employ containerization technologies such as Kubernetes and Docker for efficient deployment and scaling.
- Innovation and Problem Solving:
- Stay abreast of the latest advancements in technology, especially in the open-source GenAI community.
- Demonstrate creative problem-solving abilities and communicate complex technical concepts clearly to non-technical stakeholders.
Qualifications
- Experience:
- 8+ years in Computer Science, Engineering, or a related field, with a proven track record in full-stack development.
- Extensive experience in Python and familiarity with the entire software development lifecycle.
- In-depth knowledge of building and managing scalable systems, with hands-on experience in distributed computing and microservices architecture.
- Skills:
- Proficiency in various database technologies and a strong understanding of OOP and design patterns.
- Experience with AWS and infrastructure-as-code, alongside expertise in CI/CD and DevOps methodologies.
- Strong skills in containerization and orchestration using Kubernetes and Docker.