Graduate Analytics Internship – Summer 2027

Humana•Louisville, KY

1d•Onsite

About The Position

Become a part of our caring community. Are you ready to help shape the future of healthcare through data, analytics, and innovation? At Humana, we are committed to improving health outcomes and delivering more personalized, equitable, and effective experiences for the people and communities we serve. As a Graduate Analytics Intern, you will work at the forefront of healthcare analytics and innovation while gaining exposure to Humana’s data-driven approach to improving quality, affordability, access, and member outcomes. Interns may contribute across several key teams, including Network Adequacy and Analytics, Reliance, Quality and Cost Strategy Analytics, Medicare Supplement, Humana Military, RASA - Research and Data Science, Care Management, Policy Governance. This experience is designed to help graduate students build practical analytics capabilities while contributing to Humana’s broader commitment to improving healthcare quality and member well-being. This is a 12-week internship primarily based at Humana’s headquarters in Louisville, KY, with limited opportunities available in Arlington, VA; Chicago, IL; Ft. Lauderdale, FL; Nashville, TN; and New York, NY. The program is not offered remotely. Interns are expected to work in office 3-4 days per week based on leader & team needs.

Requirements

Currently pursuing a master’s degree in Computer Science, Data Analytics, Data Science, Biomedical Informatics, Epidemiology, Economics, Mathematics, Statistics, Biostatistics, Engineering, Actuarial Science, or a related field.
Must be a current full-time graduate student with an expected graduation date between December 2027 and Summer 2028.
Must be available to work full-time, 40 hours per week, Monday through Friday, on-site for the full 12-week internship from May 24, 2027, through August 13, 2027.
Must be willing to work in office 3-4 days per week based on leader & team needs at Humana’s headquarters in Louisville, KY, or one of our hub locations in Arlington, VA; Chicago, IL; Ft. Lauderdale, FL; Nashville, TN; and New York, NY.
Must not require sponsorship to work in the United States now or in the future.

Nice To Haves

Demonstrated programming skills in one or more analytical languages or tools, such as Python, PySpark, SAS, SQL, R, or similar technologies.
Foundational understanding of statistical analysis, data management, and analytic problem-solving.
Ability to communicate analytical findings clearly to both technical and non-technical audiences.
Experience working with complex healthcare, clinical, quality, consumer, claims, operational, or longitudinal datasets.
Ability to work with data in cloud-based or big data environments.
Experience with advanced statistical methods, such as linear and non-linear regression, survival analysis, causal inference, time-series analysis, or longitudinal analysis.
Familiarity with machine learning techniques, including supervised and unsupervised learning, ensemble methods, dimensionality reduction, graph analytics, deep learning, natural language processing, or large language models.
Experience with responsible AI practices, including model interpretability, bias assessment, validation, privacy awareness, and ethical use of data.
Experience with cloud platforms such as Azure, Google Cloud Platform, or AWS.
Big data experience using technologies such as Spark, Hive, HDFS, Databricks, or similar platforms.
Experience developing dashboards, reports, or visual storytelling using tools such as Power BI, Tableau, Python visualization libraries, SAS Visual Analytics, or similar tools.
Strong organizational skills, attention to detail, and ability to manage multiple priorities and deliverables.
Effective communication and presentation skills, including the ability to explain complex analytical concepts to diverse audiences.
Demonstrated ability to collaborate in cross-functional teams and build productive working relationships.
Proficiency in Microsoft Office applications, including Excel and PowerPoint.

Responsibilities

Develop analytical frameworks and solutions that address healthcare business challenges and support measurable outcomes.
Perform exploratory data analysis, statistical modeling, and insight generation in areas related to consumer health, healthcare quality, clinical outcomes, and well-being.
Combine and analyze diverse data sources to identify actionable insights about members, care experiences, healthcare utilization, quality outcomes, and health-related behaviors.
Develop predictive and prescriptive models that support acquisition, retention, engagement, quality improvement, loyalty, wellness, satisfaction, and sustainable health-related behavior change.
Apply machine learning, natural language processing, and large language model techniques, where appropriate, to support responsible healthcare analytics use cases.
Support development of tools and methods to identify, assess, and reduce stigmatizing or biased language in healthcare documentation using responsible AI and NLP approaches.
Create clear, compelling data visualizations and dashboards to communicate findings, trends, risks, and opportunities to business partners and leadership.
Translate complex analytical results into practical recommendations that support strategic decisions and operational improvements.
Work closely with business partners, clinicians, subject matter experts, analytics leaders, and cross-functional teams to deliver impactful, data-driven solutions.
Document methods, assumptions, limitations, and results in a clear and reproducible manner.
Demonstrate curiosity, collaboration, accountability, and a commitment to ethical, inclusive, and responsible use of data.
Use your skills to make an impact.