Public Investments Quantitative Analyst Intern, Summer 2027

Northwestern Mutual•Milwaukee, WI

2d•$17 - $30•Onsite

About The Position

Northwestern Mutual’s Public Investment Department is seeking an undergraduate-level Quantitative Analyst Intern for summer 2027. The intern will help build tools and conduct analyses that support investment processes for a department managing more than $130 billion in fixed income assets. Working with Portfolio Managers, Traders, and Credit Analysts, the intern will contribute to improvements involving relative value analysis, portfolio construction, trading tools, and risk measurement. The role is part of the Quantitative Research & Analytics team. The work spans data, modeling, visualization, and applications. It includes building and maintaining data models, developing dashboards and applications, implementing machine learning models, and applying quantitative methods to investment processes. The internship is full-time and onsite, runs from June 2027 to August 2027, and includes professional development workshops, senior leadership Q&As, volunteer initiatives, and networking and social events.

Requirements

Progress toward a bachelor’s degree in a quantitative field, such as Quantitative Finance, Computer/Data Science, Finance, or Mathematics.
Strong development skills in languages and tools such as SQL, Python, Streamlit, and dbt.
Excellent data manipulation and data visualization skills.
Passion for investing.
Effective oral and written communication skills.
Demonstrated analytical and problem-solving ability.
High degree of self-motivation, passion, and drive to learn.

Nice To Haves

Experience with software development practices such as version control and CI/CD pipelines.
Experience using Bloomberg and BlackRock Aladdin.

Responsibilities

Collaborate with data engineers to onboard data sources and design and implement dbt SQL models for data cleaning and integration.
Write data quality tests to ensure data integrity.
Create dashboards and applications using Tableau and Streamlit to communicate data and model outputs to investment professionals.
Use machine learning and AI techniques to develop predictive models, optimize model parameters, research signals, and deploy models to the Snowflake production environment.
Apply quantitative methods, including portfolio optimization, Monte Carlo simulation, risk measurement, and backtesting, to enhance investment processes.
Work with Portfolio Managers, Traders, and Credit Analysts to identify investment opportunities through efficient data delivery, advanced models, and intuitive dashboards.
Contribute to investment-process improvements such as relative value analysis, portfolio construction, trading tools, and risk measurement.