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One of Boston’s most successful Asset Management firms is seeking a Research Data Analytics Engineer to join a high performing team focused on building and maintaining research databases used in a state-of-the-art quantitative investment process.
The Analytics Engineer 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 a strong knowledge of financial data used in multi-asset class quantitative investing and have a keen interest in thinking about and solving data quality issues and be adept at using various tools and technologies at their disposal to execute the job.
Responsibilities include, but are not limited to:
- 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
- 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
Nice to have:
- 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
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Full-time
Job function
Job function
Engineering, Finance, and Information TechnologyIndustries
Investment Management, Financial Services, and Data Infrastructure and Analytics
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