2027 PhD Summer Intern – Quantitative Portfolio Management

Location: Onsite at hirify.global’s headquarters in Newport Beach, California, United States

Salary: $205,000 annual base salary, plus a discretionary bonus and a transition bonus to support relocation to an office location.

Company

hirify.global is an active fixed-income investment manager developing investment solutions and systematic strategies for clients.

What you will do

• Research systematic investment strategies spanning managed futures, alternative risk premia, and quantitative alpha.
• Work across Rates, FX, Equities, Commodities, and Volatility asset classes.
• Generate investment ideas and test signals using empirical research methods.
• Contribute to transaction cost analysis, portfolio construction, optimization, deployment, and portfolio management.
• Independently drive research projects and communicate findings through written and verbal presentations.

Requirements

• Ph.D. candidacy in a quantitative field, including Finance, Economics, Statistics, Computer Science, Operations Research, Physics, or Mathematics.
• Expected Ph.D. graduation between December 2027 and June 2028.
• Business-proficient English.
• Strong background in quantitative disciplines, with knowledge of asset pricing, economic theory, and optimization methods.
• Training in statistics and econometrics, with experience analyzing large, unstructured real-world datasets.
• Programming proficiency, with a strong preference for Python, plus excellent analytical, creative research, writing, and communication skills.

Nice to have

• Knowledge of fixed-income markets.
• Experience using emerging technologies and AI tools to solve problems in academic or professional projects.

Culture & Benefits

• Ten-week full-time internship running from early June through mid-August.
• Week-one fundamentals training, cross-divisional education, networking, and social events.
• Guidance and mentorship from a supervisor, peer mentor, senior leaders, and the team.
• Hands-on experience with AI-powered tools, supported by training and resources.
• Formal mid-summer and end-of-summer feedback, competitive compensation, and relocation assistance.

Hiring process

• Applications are reviewed in phases, with early applications encouraged for initial consideration.