Data Science Intern - Summer 2027 Intern

Sun Life•Wellesley, MA

1d•Hybrid

About The Position

The Data Science Intern will provide advanced analytics support within Sun Life’s Business Analytics function, using data and machine learning to improve business outcomes across the Health and Risk Solutions business. The intern will work with functional teams and analytic agile squads supporting AI use cases in different business domains, and will report to the Director of Advanced Analytics Transformation. The role offers the opportunity to work alongside experienced data scientists on high-impact projects. The intern will assist with developing and monitoring predictive models and AI solutions supporting pricing, underwriting, and clinical review processes. The role may also involve applying machine learning to identify opportunities to streamline and automate aspects of these processes. This is a hybrid internship, and interns must be located near a Sun Life U.S. office in Wellesley, Massachusetts; Kansas City, Missouri; Hartford, Connecticut; Portland, Maine; or Milwaukee, Wisconsin. The internship session runs from June 2027 through August 2027, and interns must be able to work 40 hours per week.

Requirements

Be currently enrolled in an accredited college or university during the internship period of June 2027 through August 2027.
Be an undergraduate or graduate student in a statistical, mathematical, or technical field such as Data Science, Computer Science, Statistics, or Actuarial Science.
Be eligible to legally work in the United States.
Be able to work full-time, 40 hours per week, during the internship session.
Have a strong academic foundation in developing and implementing data science techniques.
Have strong knowledge of statistical and data science techniques, including machine learning and data visualization, and experience with databases.
Be proficient in Python and SQL for data manipulation, modeling, and automation.
Have experience with machine learning frameworks and libraries.
Be committed to data compliance, model governance, and security protocols.
Have strong problem-solving skills and effective communication skills, including the ability to explain technical concepts to non-technical audiences.

Nice To Haves

Experience with generative AI, including prompt engineering, RAG workflows, and integrating LLMs into business processes.

Responsibilities

Support the application of data science techniques to solve business problems, including exploratory data analysis, feature engineering, predictive modeling, and visualization.
Collaborate with the team to develop, validate, and maintain robust predictive models and AI solutions.
Use structured and unstructured data and a variety of machine learning techniques to improve model performance and interpretability.
Follow team standards for writing, organizing, and documenting code so project work is reproducible and understandable.
Interpret data and model outputs to generate actionable insights and recommendations for business decisions.
Assist with developing and monitoring predictive models and AI solutions for pricing, underwriting, and clinical review processes.
Explore ways to streamline and automate aspects of business processes using machine learning.
Perform other duties as assigned.

Benefits

Generous vacation and sick time.
Paid family, parental, and adoption leave.
Medical coverage.
Company-paid life and AD&D insurance.
Disability programs.
Partially paid sabbatical program.
401(k) employer match.
Stock purchase options.
Employer-funded retirement account.
Flexible, inclusive, and collaborative work environment supporting career growth.