Position Overview:
Our client is in search of a Quantitative Full Stack Developer to collaborate closely with the Fixed Income Quant Research Team. Your role involves contributing to various projects related to the investment process, such as data loading, research tool development, model creation, and analytics. Your primary responsibility will be to shape and construct a novel data processing and modeling framework for the Fixed Income Team, utilizing Python and a cutting-edge, cloud-native scalable-computing platform. Working alongside Fixed Income Researchers and Portfolio Managers, you'll delve into all facets of the research and production model code supporting the team's investment strategies. Your work will entail gaining a deep understanding of the quantitative and economic models, as well as identifying the key inputs driving the model outputs.
Job Description:
- Quantitative Development: Enhance, develop, test, and deploy production model code to support existing research platforms and strategy/portfolio applications.
- Platform Migration: Collaborate in transitioning code to a new Python-based quant infrastructure. Recommend modern architectures by collaborating with other members of the Technology team to determine the optimal end-to-end solution.
- Software Engineering: Employ industry-standard best practices for software design, lead internal code review processes, conduct code analysis, and proactively identify software risks.
- Data Pipeline Management: Design and implement efficient end-to-end data and analytical solutions to meet internal business needs, leveraging a Python stack.
- Database Consolidation: Assist in consolidating data sources utilized by the investment team onto a shared platform. Ensure compliance with GMO's architecture best practices and coding standards during implementation.
- Team Participation: Engage actively in GMO Python/new platform working groups and contribute to agile/scrum activities.
Requirements for Success:
- A Bachelor's degree or equivalent college education is necessary.
- Preference is given to candidates with advanced degrees in computer science, engineering, math, or science.
- Familiarity with statistics and experience using optimization libraries (both open source like cvxpy and commercial solvers such as cplex and gurobi) is advantageous.
- While not mandatory, experience with Matlab is considered a bonus.
- Candidates should possess a minimum of 3-5 years of professional experience in Python, including package development.
- A solid understanding and practical application of software design principles are essential.
- Preferred experience includes working with SQL queries and developing databases using relational databases.
- Knowledge and familiarity with modern CI/CD DevOps practices and orchestration tools like Azure DevOps, Airflow, Kubernetes, and Docker are beneficial.
- Strong preference is given to candidates with experience using GIT.
