Research Systems – Full Stack Developer, Boston, GMO
Founded in 1977, GMO is a private partnership committed to delivering superior investment performance and advice to our clients. We offer strategies where we believe we are positioned to add the greatest value for our investors. These include multi-asset class portfolios as well as dedicated equity, fixed income, and absolute return offerings, many of which employ the firm’s proprietary 7-year asset class forecasting framework. Our client base is comprised primarily of institutions, including corporate and public defined benefit and defined contribution retirement plans, endowments, foundations, and financial intermediaries.
GMO, whose sole business is investment management, employs approximately 470 people worldwide and is headquartered in Boston with offices in San Francisco, London, Amsterdam, Sydney, and Singapore. We manage roughly $70 billion in client assets using a combination of top-down and bottom-up approaches that blend traditional fundamental insights with innovative quantitative methods to identify undervalued asset classes and securities. Our valuation-based approach embeds several key factors, including: a long-term investment horizon, discipline, conviction, and a commitment to research. Our research emphasizes not only identifying and exploiting pricing dislocations but also understanding the long-term drivers of return in the markets in which we invest. We are known for our candor in sharing our views with clients and for our willingness to take bold, differentiated positions when opportunities warrant.
The Investment Data Solutions (IDS) Team provides investment data, data engineering & science, quant & application development, operations and support to GMO’s investment teams in all areas of the investment process. Our work spans fundamental, market & alternative data, data warehousing on-premises & in the cloud, data quality, portfolio construction & optimization, investment analytics and more.
The team prides itself on an open culture of sharing and learning new technologies, problem solving, and comradery. We are a focused team of data & technology professionals who work in an agile framework to deliver timely and on-demand solutions using the latest cutting-edge software and methodologies. This team consists of approximately 30 technology professionals who collaborate with all investment teams in GMO (including equity, fixed income, and asset allocation teams), Performance Analytics and Business Development.
The Research Systems team forms part of IDS, and is responsible for the design, development, deployment, and support of mission critical applications in verticals of research, portfolio construction and portfolio management. This team consists of approximately 10 technology professionals whose key functions include application development, requirements analysis, system integration, application support, and production support. The business areas serviced by this team include all investment teams in GMO, Performance Analytics and Business Development.
Design and develop complex software applications supporting internal business requirements using Microsoft .NET stack, cloud technologies and/or Python stack.
Support existing applications; develop and deploy fixes.
Create new system components and enhance existing components, with a focus on TDD and SOLID principles.
Ensure that implementation adheres to architecture, best practices, and GMO’s coding standards.
Participate in code reviews, code analysis, and identification of software risks.
College degree required, preferably in computing, math or science
Advanced understanding and experience in:
– Application of Object-Oriented Analysis and Design
– Automated code testing required – Automation Testing (knowledge of BDD testing tools such as Specflow or equivalent, unit testing tool NUnit/MSTest or equivalent)
– .NET stack, C#, .Net Core, SQL Server, Release Management, GIT
– Database development (Microsoft SQL Server preferred)
– Python stack
Development experience in one or more of the following is preferred:
– Cloud technologies (Azure is preferred)
– Knowledge of Micro Services Architecture/Dockers/Containers
Excellent communication skills – both written and oral. Ability to translate requirements and proposed solutions with investment team members.
Mathematical or other analytical background strongly preferred
We anticipate the opportunity for development work in the quantitative and machine learning spaces so relevant mathematical or analytic qualifications will be helpful
Apply for the job: https://jobs.lever.co/gmo/e9a331ab-e239-4b34-ba2a-5e8be93cb2a5
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