Agile Cloud Developer

3 weeks ago


Boston MA, United States Gmo Llc. Full time

Founded in 1977, GMO is a global investment manager committed to delivering superior long-term investment performance and advice to our clients. These include multi-asset class, equity, fixed income, and alternative offerings.
We manage approximately $60bn for a client base that includes many of the world’s most sophisticated institutions, financial intermediaries, and private clients. GMO is privately owned and employs over 430 people worldwide. West Coast Hub comprised of professionals located in and around the Greater San Francisco area and a Representative Office in Tokyo. GMO’s Investment Data Solutions (IDS) Team consists of over 35 technology and data engineering professionals who partner closely with GMO’s investment managers and research teams to provide structured and unstructured market data, data engineering and analysis, quantitative application development, operations, and support in all areas of the research and investment process. Utilizing cloud-based tools and architectures, our work spans fundamental and alternative data pipeline creation, data engineering, portfolio construction, optimization, investment analytics and more.
We are a focused team of data and technology professionals who work in an agile framework to deliver timely and on-demand solutions and frameworks.
This position will partner with the Fixed Income Quant Research team which is responsible for quantitative research and systematic strategy development in rates, credit and currencies across developed and emerging markets. We are seeking a Quantitative Full Stack Developer to work closely with the Fixed Income Quant Research Team. You will work on a variety of projects focused on different aspects of the investment process, including data loading, research tools, model generation and analytics. You will help define and build a new data processing and modeling process for the Fixed Income Team using Python and a cloud-native, state of the art scalable-computing platform. Support existing research platform and strategy/portfolio applications by enhancing, developing, testing, and deploying production model code.
Platform Migration: Assist in migrating code to a new Python-based quant infrastructure. Software Engineering: Utilize industry standard best practices for software design, lead internal code review processes, provide code analysis, and proactively identify software risks.
Data Pipeline Management: Design and develop efficient end-to-end data and analytical solutions that support internal business requirements, using a Python stack.
Database Consolidation: Help consolidate data sources utilized by the investment team to a common shared platform. Ensure that implementation adheres to GMO’s architecture best practices and coding standards.
Actively participate in GMO Python/new platform working groups and engage in agile/scrum activities.
Bachelor’s or equivalent college degree required
Advanced degree in computer science, engineering, math, or science preferred
Familiarity with statistics and experience working with optimization libraries (open source optimization libraries like cvxpy, commercial solvers like cplex and gurobi) is helpful
Matlab experience a plus, not required
A minimum of 3-5 years of professional experience in Python, including package development
Solid understanding and application of software design principles
Experience with SQL queries and database development using relational databases is preferred
Experience and understanding of modern CI/CD DevOps and orchestration tools such as Azure DevOps, Airflow, Kubernetes and Docker is a bonus



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