Investment Data Analyst - Hybrid, Data Automation

New York Life Investment Management; Jersey City (NJ); Hybrid; USD 115,000 - 164,500; Full time

Job summary

New York Life Investment Management (NYLIM) is seeking an Investment Data Analyst to support data management and analytics for a broad range of investment strategies. You will create and maintain high‑quality data sets for equity, fixed income, and alternatives, working with end‑user inquiries from business, operations, and technology stakeholders.

The ideal candidate has strong SQL, Python, and data visualization familiarity, plus the ability to reconcile data across systems and automate

Qualifications

• Bachelor’s degree in Finance, Economics, Data Science or a related field.
• Minimum 3 years of experience in a quantitative role within Investment services.
• Strong knowledge of financial instruments including equities, fixed income, futures, FX, options, bank debt, swaps and other derivatives.

Responsibilities

• Ensure accuracy and integrity of investment data across internal/external systems.
• Collaborate with technology to ensure timely, accurate data delivery across systems.
• Support internal clients with reliable data for sales, marketing, risk oversight and investment teams.
• Assist in daily reporting, ensuring consistency and timely delivery of recurring portfolio reports.
• Automate end‑to‑end data processes to boost efficiency.

Skills

Financial instruments

SQL queries

Data analysis

Communication skills

Independent & team work

Performance platforms

Education

Bachelor's degree

Master's degree preferred

Tools

FactSet

Bloomberg

Aladdin

Tableau

Power BI

QlikView

Seismic LiveDocs

Vermillion

Job description

New York Life Investment Management (NYLIM) is seeking an Investment Data Analyst to support data management and analytics for a broad range of investment strategies. You will create and maintain high‑quality data sets for equity, fixed income, and alternatives, working with end‑user inquiries from business, operations, and technology stakeholders.

The ideal candidate has strong SQL, Python, and data visualization familiarity, plus the ability to reconcile data across systems and automate