Make an Impact with Data Science
Bring your curiosity, technical skills, and bold ideas to Evernorth Health Services, a division of The Cigna Group. Our Data Science Center of Expertise internship is a foundational development opportunity for emerging data science professionals ready to apply advanced analytics to meaningful healthcare challenges. You will contribute to strategically important work, learn alongside compassionate experts, and explore how innovative solutions can improve health outcomes and business decisions.
This is more than a summer project. Intern-developed solutions have evolved into enterprise capabilities, been presented to senior leadership, and, in several cases, contributed to patented innovations. You will also build relationships through professional development, networking, and direct engagement with senior data science leaders and clinical stakeholders who use analytics to shape strategic and operational decisions.
Responsibilities
- Develop and evaluate predictive, machine learning, natural language processing, or generative AI solutions that address complex healthcare and business challenges.
- Translate large, varied datasets, including claims, member information, call transcripts, surveys, and web logs, into insights that can improve member outcomes, experiences, and operational effectiveness.
- Partner with data scientists, engineers, business leaders, and clinical stakeholders to define problems, test ideas, and turn research into scalable solutions.
- Build clear, reproducible data pipelines, models, and visualizations using tools such as Python, R, SQL, Spark, or related technologies.
- Communicate findings, tradeoffs, and recommendations to technical and nontechnical audiences, including opportunities to present work to senior leadership.
- Apply a responsible, growth-oriented approach by seeking feedback, testing assumptions, documenting methods, and considering data quality, privacy, fairness, and model performance.
Past projects have included predictive models to improve member health outcomes; real-time NLP platforms that categorize member feedback; conversational AI solutions; transformer-based models for call topic classification; and research using optical character recognition and large language models to extract clinical entities from physician fax documents.
Required Qualifications
- Pursuing a master's degree or PhD in data science, statistics, applied mathematics, computer science, bioinformatics, computational linguistics, or another quantitative field.
- At least 1 year of hands-on data science or analytics experience gained through coursework, research, internships, or professional projects.
- Working knowledge of Python or R, probability and statistics, and data preparation, cleansing, and interpretation.
- Experience developing or evaluating analytical methods such as regression, decision trees, clustering, machine learning, text mining, or natural language processing.
- Ability to explain technical work clearly, collaborate across disciplines, and adapt based on feedback and new information.
Preferred Qualifications
- Experience querying relational or distributed datasets using SQL, Hive SQL, Spark, PySpark, Scala, Hadoop, or HDFS.
- Experience with visualization tools or libraries such as Tableau, Shiny, ggplot, or Matplotlib.
- Demonstrated interest in healthcare analytics, responsible AI, experimentation, or translating research into practical solutions.
Additional Information
Location: Interns are expected to work a hybrid schedule, spending three days per week in our Morris Plains, NJ, Austin, TX, or St. Louis, MO office and two days working remotely.
Compensation: Hourly pay ranges from $35.00-$43.00, based on degree program, and year of study.
Work Authorization: Candidates must be authorized to work in the United States and not require current or future employment sponsorship.
Enterprise Intern Schedule: This is a full-time summer internship (40 hours per week) running from May 24 through August 13th
If you will be working at home occasionally or permanently, the internet connection must be obtained through a cable broadband or fiber optic internet service provider with speeds of at least 10Mbps download/5Mbps upload.
About The Cigna Group
Doing something meaningful starts with a simple decision, a commitment to changing lives. At The Cigna Group, we're dedicated to improving the health and vitality of those we serve. Through our divisions Cigna Healthcare and Evernorth Health Services, we are committed to enhancing the lives of our clients, customers and patients. Join us in driving growth and improving lives.
Qualified applicants will be considered without regard to race, color, age, disability, sex, childbirth (including pregnancy) or related medical conditions including but not limited to lactation, sexual orientation, gender identity or expression, veteran or military status, religion, national origin, ancestry, marital or familial status, genetic information, status with regard to public assistance, citizenship status or any other characteristic protected by applicable equal employment opportunity laws.
If you need a reasonable accommodation to complete the online application process, please email seeyourself@thecignagroup.com for assistance. Please note that this email inbox is dedicated to accommodation requests only and cannot provide application updates or accept resumes.
The Cigna Group has a tobacco-free policy and reserves the right not to hire tobacco/nicotine users in states where that is legally permissible. Candidates in such states who use tobacco/nicotine will not be considered for employment unless they enter a qualifying smoking cessation program prior to the start of their employment. These states include: Alabama, Alaska, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Iowa, Kansas, Maryland, Massachusetts, Michigan, Nebraska, Ohio, Pennsylvania, Texas, Utah, Vermont, and Washington State.
Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances.
