Quantitative Research Data Engineer

godirect; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Voya Investment Management is seeking a Quantitative Research Analyst for its Systematic Equities team. You will support data, research, and production infrastructure that underpins the systemic investment process.

The role sits at the intersection of data science and investment analysis, working with researchers and PMs to identify alpha opportunities. You will build data pipelines, maintain codebases, and explore new data sources.

Qualifications

• Degree in a quantitative discipline such as Financial Engineering, Operations Research, Mathematics, Computer Science, Statistics, etc.
• 0-5 years of relevant work experience in applied quantitative research, preferably investment management.
• Strong analytical and mathematical skills with econometrics knowledge.
• Hands-on experience with Python (numpy/pandas, ML packages) and relational databases.
• Experience with cloud services (Azure) and financial datasets (FactSet, Bloomberg).

Responsibilities

• Build, maintain and monitor reliable data pipelines supporting quantitative research and production models.
• Maintain and advance the team’s shared codebase, data repositories, and cloud-based technology stack.
• Clean, validate and evaluate new data sets for potential alpha generation.
• Advance multi-factor and machine intelligence models with new signals and estimation techniques.
• Collaborate with portfolio managers, researchers, tech partners, and analysts.
• Contribute to product development with client-facing and product teams.
• Contribute to thought leadership articles to share investment philosophies and capabilities.

Skills

Python

Statistics

Econometrics

Data analysis

Analytical thinking

Education

Quantitative degree

CFA candidate

Tools

Azure

FactSet

Bloomberg

SQL

Job description

Voya Investment Management is seeking a Quantitative Research Analyst for its Systematic Equities team. You will support data, research, and production infrastructure that underpins the systemic investment process.

The role sits at the intersection of data science and investment analysis, working with researchers and PMs to identify alpha opportunities. You will build data pipelines, maintain codebases, and explore new data sources.