Research and Investment Data Analyst

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 $65bn 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. We are headquartered in Boston, with additional offices in Europe, Asia and Australia. 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. 
Position OverviewWe are looking for a Research and Investment Data Analyst to join a high performing team focused on building and maintaining research databases used in a state-of-the-art quantitative investment process.  This person will act as the first responder for data quality monitoring and resolution of all daily and monthly processing. They will monitor, develop, and enhance data quality controls and processes across the platform.
This position offers a unique opportunity to learn about all facets of data used in the investment process. An ideal candidate should have a working knowledge of financial data used in a multi-asset class quantitative investment process and have a strong desire to think about and solve data quality issues and be adept at using various tools and technologies at their disposal to execute the job.

Key Responsibilities

• Monitor incoming data to detect anomalies and remediate issues.
• Investigate and resolve data quality questions and concerns.
• Develop an expert understanding of internal databases and processes and ensure information is maintained accurately and efficiently.
• Become a “subject matter expert” in a variety of data categories (reference, market, fundamental, estimate, macro-economic, et al) across various asset classes including equity and fixed income.
• Develop a keen understanding of how data is utilized in our investment processes to help design and implement new data sets and processes.
• Partner with investment teams and respond to and proactively address their data needs.
• Design and build efficient and effective controls to help resolve and identify potential data issues.
• Coordinate with engineering team to identify ways to improve our data and monitoring processes.
• Work with external market data vendors to bring in any new data sources required by the business users and support existing feeds.

Required

• Bachelor’s degree, preferably in economics, statistics, computer science or math
• Attention to detail
• At least One Year Working Experience with MS SQL
• At least Two Years’ Experience with Python
• 3+ years of experience with financial data
• Experience working with large data sets
• Experience with building data quality controls and resolving data issues, Passionate about robust quantitative analysis
• Strong communication skills
• High energy and positive attitude – candidate should be conscientious, self-directed and possess a strong work ethic.
• Strong interest in databases and database technologies

Plus

• Experience with data systems implemented in the cloud using Delta Lake, Spark
• Experience with Data Governance toolsets
• Interest in, or experience with, Machine Learning for Anomaly Detection