We are in search of a skilled Quantitative Full Stack Developer to join our Fixed Income Quant Research Team. As an integral part of this team, you will engage in diverse projects spanning various aspects of the investment process, including data loading, research tool enhancement, model generation, and analytics. Your primary objective will be to spearhead the development of a novel data processing and modeling framework for the Fixed Income Team, leveraging Python and a cutting-edge, cloud-native scalable-computing platform. Collaborating closely with Fixed Income Researchers and Portfolio Managers, you will address all facets of research and production model code, crucial to bolstering the team's investment strategies. Moreover, you will cultivate a deep quantitative and economic insight into the models, discerning the pivotal inputs steering model outputs.
Responsibilities:
- Quant Development: Enhance, develop, test, and deploy production model code to bolster existing research platforms and strategy/portfolio applications.
- Platform Migration: Aid in transitioning code to a new Python-based quant infrastructure, while advocating modern architecture through collaboration with Technology team members.
- Software Engineering: Implement industry-standard best practices for software design, oversee internal code review processes, conduct code analysis, and proactively identify software risks.
- Data Pipeline Management: Architect and implement efficient end-to-end data and analytical solutions to meet internal business requirements, employing a Python stack.
- Database Consolidation: Assist in consolidating data sources used by the investment team onto a shared platform, ensuring adherence to GMO's architecture best practices and coding standards.
- Team Participation: Actively engage in GMO Python/new platform working groups and contribute to agile/scrum activities.
Requirements:
- Bachelor's or equivalent college degree is mandatory.
- An advanced degree in computer science, engineering, math, or science is preferred.
- Familiarity with statistics and experience in working with optimization libraries (both open-source like cvxpy and commercial like cplex and gurobi) is advantageous.
- Experience with MATLAB is beneficial but not obligatory.
- A minimum of 3-5 years of professional experience in Python, including package development, is required.
- Solid understanding and application of software design principles are essential.
- Preference given to candidates with experience in SQL queries and relational database development.
- Bonus points for familiarity with modern CI/CD DevOps and orchestration tools such as Azure DevOps, Airflow, Kubernetes, and Docker.
- Strong preference for candidates with experience using GIT.
