Quantitative Research Analyst - Data & Alpha Signals

Voya Financial; New York (NY); On-site; USD 120,000 - 140,000; Full time

Benefits offered by this job

Health insurance

401(k) Savings plan

Tuition reimbursement

Job summary

Voya Financial seeks a Quantitative Research Analyst to join the Systematic Equities team. You will help build data pipelines, support production models, and contribute to alpha-generating research alongside researchers, engineers, and portfolio managers.

You'll work within a data-driven environment that blends data science with investment analysis, leveraging Python, ML libraries, and cloud services to advance our systematic investment process and risk management capabilities.

Qualifications

• Degree in a quantitative discipline (e.g., Financial Engineering, Mathematics, Computer Science). CFA is a plus.
• 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) and ML libraries; relational databases.
• Bonus for cloud services experience (Azure) and data sources like FactSet/Bloomberg.

Responsibilities

• Build, maintain and monitor data pipelines for research and production models.
• Maintain and advance the team’s shared codebase, data repos and cloud stack.
• Evaluate new data sets for potential alpha generation.
• Work on alpha-generating research and portfolio management processes.
• Collaborate with portfolio managers, researchers and technologists.

Skills

Python

Data analysis

Communication

Education

Quantitative degree (e.g., Financial Engineering/Math/CS)

Tools

Azure

SQL

XGBoost

SciKit-Learn

Job description

Voya Financial seeks a Quantitative Research Analyst to join the Systematic Equities team. You will help build data pipelines, support production models, and contribute to alpha-generating research alongside researchers, engineers, and portfolio managers.

You'll work within a data-driven environment that blends data science with investment analysis, leveraging Python, ML libraries, and cloud services to advance our systematic investment process and risk management capabilities.