Northwestern Mutual's Public Investment Department seeks a Quantitative Analyst Intern to build tools and conduct analyses to shape investment processes, manage fixed income assets, and drive investment performance through innovative improvements.
Requirements
- Strong development skills in languages such as SQL, Python, Streamlit, dbt, etc.
- Excellent data manipulation and data visualization skills.
- Experience with software development practices such as version control and CI/CD pipelines is preferred.
- Experience using Bloomberg and BlackRock Aladdin is a plus.
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.
Other
- Progress towards a Bachelor’s degree in a quantitative field (e.g., Quantitative Finance, Computer/Data Science, Finance, Mathematics).
- Passion for the art and science of investing.
- Effective oral and written communication skills.
- Demonstrated analytical and problem-solving ability.
- High degree of self-motivation, passion, and a drive to learn.
