Public Investments Quantitative Analyst Intern, Summer 2027

Northwestern Mutual•Milwaukee, WI

1d•Onsite

About The Position

Northwestern Mutual's Public Investment Department seeks a Quantitative Analyst Intern to join us for the summer of 2027. This role is pivotal in building tools and conducting analyses that help shape investment processes. The department manages over $130 billion in fixed income assets, and the intern will collaborate directly with Portfolio Managers, Traders, and Credit Analysts to develop cutting-edge solutions. The intern will leverage their strengths and interests in a flexible role spanning data, modeling, visualization, and applications, focusing on driving investment performance through innovative improvements to investment processes such as relative value analysis, portfolio construction, trading tools, and risk measurement.

Requirements

Progress towards a Bachelor’s degree in a quantitative field (e.g., Quantitative Finance, Computer/Data Science, Finance, Mathematics).
Strong development skills in languages such as SQL, Python, Streamlit, dbt, etc.
Excellent data manipulation and data visualization skills.
Demonstrated analytical and problem-solving ability.
High degree of self-motivation, passion, and a drive to learn.

Nice To Haves

Experience with software development practices such as version control and CI/CD pipelines is preferred.
Experience using Bloomberg and BlackRock Aladdin is a plus.
Passion for the art and science of investing.
Effective oral and written communication skills.

Responsibilities

Build & maintain data models: Collaborate with data engineers to onboard new data sources, design and implement dbt SQL models for data cleaning and integration, and write robust data quality tests to ensure data integrity.
Develop interactive data visualizations: Create insightful dashboards and applications using Tableau and Streamlit to effectively communicate data and model outputs to the department’s investment professionals.
Design and implement machine learning models: Utilize machine learning and AI techniques to develop predictive models, optimize model parameters, research new signals, and deploy models into the Snowflake production environment.
Apply quantitative methods: Leverage quantitative methods such as portfolio optimization, Monte Carlo simulation, risk measurement, and backtesting to enhance various aspects of the investment process.
Collaborate effectively: Work closely with Portfolio Managers, Traders, and Credit Analysts to better identify attractive investment opportunities through efficient data delivery, advanced models, and intuitive dashboards.