Data Science Intern – Summer

Come join one of America’s fastest-growing insurance companies. Since 1848, National Life Group has aimed to keep our promises, providing families with stability in good times and in bad. Throughout that history, we have provided peace of mind to those families as they plan their futures.

Our mission extends beyond the insurance and annuities policies that we offer. We strive to make the world a better place through our grants from our charitable foundation, paid volunteer time for our employees, environmentally sustainable and healthy workplaces, and events that promote the work of nonprofits in our own backyard.

We foster a collaborative environment with opportunities for growth and encourage our associates to live our values:
Do good. Be good. Make good.

Please note that we do not offer visa sponsorship for this position.

At National Life Group, we are unlocking the power of data and AI to transform our business and enhance customer experience. Our AI Center of Excellence (AICoE) is leading this effort through innovations in machine learning, advanced analytics, and generative AI.

As a Data Science Intern, you will contribute to projects within our AI CoE. You’ll gain hands‑on experience applying computer science and data science techniques to real business challenges. Projects may range from supporting the development of predictive models to testing and enhancing generative AI solutions.

This is a unique opportunity to explore both traditional data science methods and emerging AI technologies while working in a collaborative, mission‑driven environment.

In this role, you will collaborate with AI and data science practitioners, technical experts, and business partners. You will work primarily in National Life’s Databricks environment to develop and evaluate data-driven solutions. Depending on project priorities, responsibilities may include:

• Prepare, explore, and validate datasets and features for life insurance and annuity use cases such as surrender propensity, premium persistency, and policyholder behavioral analysis.
• Support the development and evaluation of statistical and machine‑learning models, comparing results with established baselines and investigating errors and limitations.
• Help design experiments and analyze business outcomes using appropriate comparisons, sound statistical methods, and clear measures of success.
• Develop reusable Python and SQL workflows, including validation checks and documentation that allow others to review and reproduce the work.
• Prototype and evaluate generative AI applications, assessing output quality, source support, failure modes, and practical business usefulness.
• Apply responsible AI and data‑handling practices, including appropriate treatment of sensitive information and validation of AI‑generated outputs.
• Communicate findings and recommendations to technical and business audiences.

• Currently pursuing a bachelor’s or master’s degree in computer science, data science, mathematics, statistics, or a related field.
• Strong programming skills in Python, with experience using data analysis or machine‑learning libraries such as pandas and scikit‑learn. Exposure to Apache Spark, PyTorch, or Tensor Flow is a plus.
• Working knowledge of SQL, including querying, joining, and aggregating data to prepare and validate datasets for analysis and modeling.
• Familiarity with foundational statistical and machine‑learning concepts, including regression, classification, model evaluation, and hypothesis testing.
• Coursework or projects integrating generative AI APIs into software is a plus.
• Curiosity and eagerness to learn about the real‑world application of both modern AI technologies and foundational statistical methods.
• Strong…