Data Analyst

C2R Ventures; Boston; On-site; USD 80,000 - 120,000; Full time

Job summary

A leading asset management firm in Boston is looking for a Research Data Analyst to enhance their quantitative investment process. This role involves managing data quality, developing controls, and collaborating with investment teams to streamline data usage in investment decisions. Ideal candidates should possess a strong financial data background and proficiency in relevant technologies.

Benefits

Flexible working arrangements

Professional development opportunities

Qualifications

• 5+ years of experience working with financial data.
• Experience orchestrating data pipelines.
• Proficient in Python and SQL.

Responsibilities

• Monitor incoming data to detect anomalies and remediate issues.
• Investigate and resolve data quality questions and concerns.
• Design and build efficient controls to help resolve and identify potential data issues.

Skills

Financial data expertise

Data quality resolution

Data visualization

Data pipeline orchestration

Python

SQL

Education

Bachelor’s degree in Economics, Statistics, Computer Science, Math, or Information Systems

Tools

Apache Airflow

Databricks

Delta Lake

Spark

Job description

One of Boston’s most successful Asset Management firms is seeking 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 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

In order to qualify:

• 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