Research 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.
Please follow the prompts included in this job posting to apply. The application window for this role is anticipated to remain open until the job is filled, or as otherwise determined by GMO. 
Position Overview We are looking for a Research 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. The Analyst will be responsible for resolving data quality issues, building new data quality controls, onboarding new datasets, creating documentation, and making data access more transparent. This position offers a unique opportunity to leverage one’s experience and have an impact on how data is used in the research and investment process. An ideal candidate should have strong knowledge of financial data used in multi-asset class quantitative investing and have a keen interest 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 to proactively address their data needs
• Design and build efficient and effective controls to help resolve and identify potential data issues
• Coordinate with the data engineering team to identify ways to improve our data and monitoring processes
• Work with external market data vendors to bring in new data sources required by business users and support existing feeds
• Create documentation to support data processing and exploration
• Contribute to a rotational “on call” program to facilitate the overnight processing of data

Requirements

• Bachelor’s degree, preferably in economics, statistics, computer science, math or information systems
• 5+ years of experience working with financial data at an asset management company or financial data provider
• Experience orchestrating data pipelines and processes using Apache Airflow
• Proficient using Python and SQL to maintain data quality and automate data workflows
• Experience modeling data based on vendor methodologies and internal use
• Experience building data quality controls and resolving data issues
• Proven ability to visualize data using modern data analysis techniques
• Strong attention to detail
• Strong communication skills
• High energy and positive attitude – candidate should be conscientious, self-directed and possess a strong work ethic
• Passionate about a data focused career path
• Strong interest in databases and database technologies

Plus:

• Understanding of LLMs and Generative AI – Ability to evaluate and apply large language models for tasks such as data summarization, anomaly detection, or intelligent alerting.
• Prompt Engineering – Skill in crafting effective prompts to extract insights, automate documentation, and enhance data workflows using AI tools.
• Experience with data systems implemented in the cloud using Databricks, Delta Lake, Spark
• Experience with Data Governance toolsets
• Interest in, or experience with, Machine Learning for Anomaly Detection

GMO is committed to the recruitment, employment, and promotion of all candidates equally, regardless of an individual's gender, race, color, national origin, ancestry, age, religion, pregnancy, marital status, sexual orientation, gender identity or expression, military or veteran status, genetic information, physical or mental disability (except where such disability is a bona fide occupational disqualification) or any other classification protected under federal, state or local law.