Quantitative Developer

Company Profile

Founded in 1977, GMO is a global investment manager committed to delivering superior long-term investment performance and advice to our clients. We offer strategies and solutions where we believe we are positioned to add the greatest value for our investors. 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. Industry-wide, we are well known for our focus on valuation-based investing, willingness to take bold positions when conditions warrant, and candid and academically rigorous thought leadership. Jeremy Grantham, GMO’s Co-Founder and Long-Term Investment Strategist, is renowned as an expert in identifying speculative investment bubbles and also as a leading climate investor and advocate.

GMO is privately owned and employs over 430 people worldwide. Headquartered in Boston, we also have offices in San Francisco, London, Amsterdam, Singapore, Sydney, and Tokyo (a representative office). Our company-wide culture emphasizes commitment to clients, intellectual curiosity, and open debate. We celebrate and respect our differences, while embracing and valuing what each of us brings to work, as we know that diverse teams in an inclusive, caring environment achieve higher engagement and better client results.

Department Profile 

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. 

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. The team values their culture of intellectual curiosity, debate, respectful disagreement, candor, and collegiality. 

Position Overview

We are seeking a Quantitative Full Stack Developer to work as an embedded resource 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. You will work closely with Fixed Income Researchers and Portfolio Managers and focus on all aspects of the research and production model code that support the team’s investment processes. You will develop a thorough quantitative and economic understanding of the models, and a comprehension of what inputs drive the model outputs.

Responsibilities

• Quant Development: 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. Suggest modern architectures by partnering with other Technology team members to ascertain the best end-to-end solution. 
• 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. 
• Team Participation: Actively participate in GMO Python/new platform working groups and engage in agile/scrum activities. 

Requirements

• 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 
• Experience with GIT is strongly preferred