Quantitative Research Intern - Multi-Asset Allocation

Principal Financial Group; New York, Des Moines (NY, IA); On-site; USD 40,000 - 55,000; Full time

Benefits offered by this job

Lump-sum stipend

Internship program

Job summary

Principal Asset Management, a subsidiary of Principal Financial Group, invites applications for the Summer 2027 Quantitative Analyst Intern role in New York City. You will support research and portfolio analysis across global equities, fixed income, currencies, and commodities, collaborating with the investment team.

You will leverage Python and SQL, conduct backtesting and risk analysis, and help enhance data-driven workflows.

Qualifications

• Pursuing a Bachelor’s, Master’s, or PhD in a quantitative field (e.g., Financial Engineering, Finance, Economics, Mathematics, Statistics, CS)
• Proficiency in Python; familiarity with SQL
• Strong interest in quantitative investing and global macro/multi-asset strategies
• Strong analytical and problem-solving skills with the ability to work with large datasets
• Availability to work full-time and onsite in New York City, NY or Des Moines, IA during Summer 2027

Responsibilities

• Conduct quantitative research and analyze financial and macroeconomic data
• Support development, testing, and evaluation of systematic investment signals and portfolio models
• Perform backtesting, performance attribution, risk analysis, and portfolio diagnostics
• Work with large financial datasets and help improve research workflows
• Summarize research findings and present results to portfolio managers and investment team members

Skills

Python

SQL

Quantitative research

Data analysis

Large datasets

Communication skills

Education

Bachelor's/Master's/PhD in a quantitative field

Tools

Bloomberg

FactSet

Job description

Principal Asset Management, a subsidiary of Principal Financial Group, invites applications for the Summer 2027 Quantitative Analyst Intern role in New York City. You will support research and portfolio analysis across global equities, fixed income, currencies, and commodities, collaborating with the investment team.

You will leverage Python and SQL, conduct backtesting and risk analysis, and help enhance data-driven workflows.