Quantitative Intern - Portfolio Engineering and Analytics

Invesco • Boston, MA

22h • Onsite

About The Position

The Quantitative Intern will join Invesco’s Portfolio Construction and Engineering team in Boston for a summer internship. The role offers the opportunity to work closely with senior team members, engage with financial technology, and complete rigorous quantitative analysis assignments. The intern may contribute to research and development in strategic, risk-aware and dynamic, macro-regime-driven asset allocation; portfolio construction and optimization; and risk modeling for public and private assets.

The Portfolio Construction and Engineering team combines quantitative finance, technology, and financial research. Its work includes building multi-asset portfolio construction models, creating systematic fixed-income portfolios, and managing risk models for public and private assets. The team also developed Vision, a cloud-based investment management platform that provides institutional and retail clients with an overview to support investment decisions.

The internship is based in Invesco’s Boston office. Under the workplace policy described in the posting, employees are expected to spend at least four full days each week in an Invesco office. Relocation and housing are not included if an offer is extended. This is a student/intern fixed-term role, and the intern must return to study after the internship.

Requirements

• Be enrolled in a master’s or PhD program in a quantitative discipline, such as engineering, financial engineering, financial mathematics, operations research, statistics, applied mathematics, computer science, or a related field, and return to study after the internship.
• Have strong programming skills in Python, including NumPy, pandas, and SciPy.
• Have a solid foundation in statistics, probability, and optimization, and be able to translate abstract principles into systematic, algorithmic representations.
• Have experience managing and manipulating large datasets, preferably using SQL, including working with unstructured data and transforming it into analysis-ready formats.
• Demonstrate an interest in finance, economics, and capital markets, and working familiarity with mean-variance optimization, factor models, and standard risk and performance metrics.
• Demonstrate very strong attention to detail and an internal drive to sanity-check and triangulate results.
• Be able to work in Invesco’s Boston office.
• Be able to prioritize work and allocate time efficiently to maximize impact.
• Have strong interpersonal and partnership skills, and communicate technical results clearly in writing and verbally to non-technical audiences.
• Be a self-starter who desires to excel and can thrive in a fast-paced environment.

Nice To Haves

• Exposure to scikit-learn, PyTorch, or TensorFlow.
• Familiarity with Git and collaborative development workflows, including code review and CI/CD.
• Familiarity with cloud environments such as AWS or Azure.
• Exposure to building or consuming RESTful services, such as FastAPI, and to front-end or visualization work in JavaScript.
• Coursework or project experience with Large Language Models and agentic AI tooling, such as LangChain, RAG, and vector databases.
• Exposure to third-party risk models such as BarraOne or Axioma.
• Progress toward the CFA designation.

Responsibilities

• Work closely with senior members of the Portfolio Construction and Engineering team.
• Complete rigorous quantitative analysis assignments.
• Help expand the team’s knowledge and capabilities in strategic and dynamic asset allocation research, portfolio construction and optimization, and risk modeling for public and private assets.

Benefits

• Company networking events with other interns.
• Peer Sponsor Program.
• Leadership Connection series.
• Virtual Lunch and Learns.
• Invesco Cares volunteer events.
• Complimentary coffee and snacks.
• 401(k) matching of 100% up to the first 6%, with a discretionary supplemental contribution.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern