Quantitative Data & Machine Learning Associate

Northwestern Mutual - Milwaukee, WI

Full-time - Mid Level

Milwaukee, WI

Insurance Carriers and Related Activities

About the position

Northwestern Mutual's Public Investment Department is seeking a Quantitative Data & Machine Learning Associate to join our dynamic team. This role is pivotal in shaping the future of our investment processes as we manage over $125 billion in fixed income assets. The successful candidate will collaborate closely with Portfolio Managers, Traders, and Credit Analysts to develop innovative data and machine learning models that enhance our investment strategies. This position offers a unique opportunity to leverage your strengths in a flexible role that encompasses data analysis, modeling, and visualization, all aimed at driving investment performance through improvements in our investment processes. In this role, you will be responsible for building and maintaining data models by collaborating with data engineers to onboard new data sources, designing and implementing dbt SQL models for data cleaning and integration, and writing robust data quality tests to ensure data integrity. You will also develop interactive data visualizations, creating insightful dashboards and applications using Tableau and Streamlit to effectively communicate data and model outputs to the investment professionals in the department. Additionally, you will design and implement machine learning models utilizing state-of-the-art techniques to develop predictive models, optimize model parameters, research new signals, and deploy models into the Snowflake production environment. Your expertise in quantitative methods such as portfolio optimization, Monte Carlo simulation, risk measurement, and backtesting will be crucial in enhancing various aspects of the investment process. You will actively identify opportunities to improve existing systems and workflows, contributing to the prioritization of system enhancements. Collaboration is key, as you will work closely with investment professionals to expedite decision-making and identify attractive investment opportunities through efficient data delivery, advanced models, and intuitive dashboards.

Responsibilities

• Leverage unique strengths and interests within a flexible role that spans data, modeling, and visualization.
• Drive investment performance through innovative improvements to investment processes such as relative value analysis, portfolio construction, and trading tools.
• Build and maintain data models by collaborating with data engineers to onboard new data sources and design dbt SQL models for data cleaning and integration.
• Write robust data quality tests to ensure data integrity.
• Develop interactive data visualizations using Tableau and Streamlit to communicate data and model outputs effectively.
• Design and implement machine learning models using advanced techniques to develop predictive models and optimize model parameters.
• Research new signals and deploy models into the Snowflake production environment.
• Utilize quantitative methods like portfolio optimization, Monte Carlo simulation, risk measurement, and backtesting to enhance investment processes.
• Identify opportunities to improve existing systems and workflows, contributing to the prioritization of system improvements.
• Collaborate effectively with Portfolio Managers, Traders, and Credit Analysts to speed up decision-making and identify attractive investment opportunities.

Requirements

• Master's degree in a quantitative field (e.g., Finance, Data Science, Mathematics) is preferred; Bachelor's degree will be considered.
• 3-7 years of relevant experience; exceptional recent graduates may be considered.
• Strong coding skills in SQL and Python.
• Expertise in data manipulation, data visualization, and machine learning.
• Familiarity with Excel, Snowflake, Streamlit, Git, dbt, and CI/CD pipelines.
• Experience using Bloomberg and BlackRock Aladdin is a plus.
• Investment-related experience and progress towards the CFA designation is preferred.

Nice-to-haves

• Experience with advanced machine learning techniques.
• Familiarity with financial modeling and investment analysis.
• Knowledge of fixed income markets and investment strategies.

Benefits

• Competitive salary based on geographic location and experience.
• Comprehensive health insurance coverage.
• 401(k) retirement savings plan with company matching contributions.
• Flexible work arrangements including hybrid options.
• Professional development opportunities and support for continuing education.