Data Science Internship, Summer 2026

Northwestern Mutual•Milwaukee, WI

1d•$17 - $30•Onsite

About The Position

At Northwestern Mutual, we are strong, innovative and growing. We invest in our people. We care and make a positive difference. Full-time onsite 10 week summer internship program, in Milwaukee, WI, Franklin, WI, or New York City, NY. Relocating interns eligible for travel and housing reimbursement. Gain exposure to real-world business perspectives through hands-on learning and meaningful work. Participate in professional development workshops, Q&A sessions, volunteer initiatives, and networking events. Data Science/Analytics Internship Work within the Core Data & Analytics function alongside your hiring manager, mentor, and team to complete tasks critical for Northwestern Mutual's success. See below for further details on each role: Data Scientist - Participate in a team that delivers quantitative and qualitative data analysis. You’ll apply and integrate sophisticated statistical, mathematical, data mining, predictive modeling, and business analysis to discover and identify new insights. A data scientist intern will interpret available internal and external data resources to develop and deliver information solutions by testing hypotheses and analyzing test results, providing the vital analytical difficulty to ensure data quality, consistency, repeatability, and accuracy of insights. Data Analyst – Support workstreams develop data driven solutions by tying quantitative measures to key business issues. This includes deriving insights from data and use visualizations to answer key business questions. Through team exposure and interaction with internal business clients, you will be able to influence others by story-telling through data, visualizing recommendations for forecasts, metrics, and sophisticated data sets. Interns will produce concrete reports that show key performance indicators, identify areas of improvement for current operations, and display root cause analysis of business problems. Bring Your Best! What this role needs.

Requirements

Pursuing bachelor's or Master’s degree in Data Science, Computer Science, Information Systems, Mathematics, Statistics, Software Engineering, Computer Engineering, Information Technology, or related field from an accredited college or university
Cumulative grade point average of 3.0 or higher
Previous work or classroom experience in one or more of the following: SQL, R, Java, Python, Tableau, Power BI, and other data & visualization tools
Employer immigration sponsorship is not available for this role

Nice To Haves

Previous software engineering or data-focused internship and/or relevant project experience
Effective oral and written communication skills
Self-starter, goal-directed, resourceful, analytical, innovative, and intellectually curious
Proven analytical and problem-solving ability
High degree of self-motivation, passion, and drive to learn
Ability to balance multiple priorities
SQL skills and understanding of ETL processes preferred
Tackle proficiency in network, software, and hardware issues
Experience sourcing, cleansing, and combining datasets from various sources
Passion for problem-solving, research, quantitative analysis, and analytical techniques
Highly organized with meticulous attention to detail

Responsibilities

Participate in a team that delivers quantitative and qualitative data analysis.
Apply and integrate sophisticated statistical, mathematical, data mining, predictive modeling, and business analysis to discover and identify new insights.
Interpret available internal and external data resources to develop and deliver information solutions by testing hypotheses and analyzing test results
Ensure data quality, consistency, repeatability, and accuracy of insights
Support workstreams develop data driven solutions by tying quantitative measures to key business issues.
Derive insights from data and use visualizations to answer key business questions.
Influence others by story-telling through data, visualizing recommendations for forecasts, metrics, and sophisticated data sets.
Produce concrete reports that show key performance indicators, identify areas of improvement for current operations, and display root cause analysis of business problems.