Quantitative Investment Research Co-op (Equities)

Ameriprise Financial Services, LLC•Boston, MA

5d•Hybrid

About The Position

This is an exciting opportunity to develop your skills, expand your network, and explore what's possible across a global financial services organization. As a Quantitative Equity Research Co-op, you will work with researchers and portfolio managers supporting systematic equity strategies. You will apply quantitative analysis, technology, and creativity to research investment ideas, develop stock selection signals, and support portfolio implementation. This six-month co-op provides hands-on experience across the quantitative investment process and the opportunity to contribute directly to active research initiatives on a team of seven investment professionals.

Requirements

Pursuing a bachelor’s degree in Statistics, Applied Mathematics, Quantitative, finance, Economics, Computer Science, Business, or related field
Graduation date of December 2027 or May/June 2028
Passionate about the investment management industry and dedication to being a part of a successful team.
Applicants must have a valid work authorization that does not now, or in the future, require visa sponsorship for employment in the United States (e.g., H-1B, F-1 CPT, F-1 OPT, TN).

Nice To Haves

Proficient programming skills in R, Python, SQL, or similar
High degree of self-motivation with strong integrity and ethics
Attention to detail
Excellent communication, interpersonal, and presentation skills
Ability to multi-task, problem solve independently and think creatively
Proven organization skills and ability to manage time effectively
Experience with large dataset manipulation and statistical analysis

Responsibilities

Monitor and analyze factor and model performance and contribute to regular performance reporting
Present research findings to team members and key stakeholders
Collaborate with investment teams, data science, and technology partners to support research initiatives
Work independently on impactful research and development projects.
Pre-process large data sets for signal processing and model estimation, including validation, cleaning, normalization, dimension reduction and visualization.
Apply innovative techniques such as machine learning and generative artificial intelligence to uncover differentiated investment signals and enrich our stock selection models.
Contribute to the team’s development of advanced investment analytics.
Work with portfolio managers to analyze market dynamics and their impact on factor behavior and portfolio performance.