Looking for an internship program where you'll make a real difference – rather than just completing busy work? Then you've come to the right place. The Cigna Group’s Summer Internship Program is designed to assign you projects that have a lasting impact on our business – which touches millions of people across the globe. 
 

As an intern, you'll get an inside look at your desired field, while working next to some of the best in the industry. Program activities, including an executive speaker series, volunteer events, and career development workshops, give you the opportunity to network with employees across the organization and prepare you for a full-time career.

Where You’ll Work

Evernorth Health Services, a division of The Cigna Group, is seeking 2025 Summer Interns who have a passion for applying advanced analytics and data science to healthcare’s biggest challenges.  Evernorth Health Services creates pharmacy, care and benefits solutions to improve health and increase vitality. We relentlessly innovate to make the prediction, prevention and treatment of disease more accessible to millions of people.

What You’ll Do

The Data Scientist Internship is an exciting opportunity to be part of Enterprise Data Science team at Evernorth Health Services. The internship will involve using data science techniques that include predictive modeling, machine learning, text mining, segmentation and clustering to help in developing solutions to increase revenue and improve Member Experience. Utilize machine learning for developing next generation of predictive models for targeted business solutions. Support the team in application of Text Mining to mine Voice of Customer data. Develop supervised / unsupervised algorithms, Big Data pipelines for making business processes efficient.

At Evernorth Health Services, interns will get a chance to work with a variety of large datasets including pharmacy and medical claims transactions, member information, voice call transcripts, survey data, web log data, etc.

• Previous project examples:

  Develop Next Generation Supervised Machine Learning Clinical models to predict Medical Non-Adherence

  Training of call classification unsupervised topic models using big data platforms such as Spark and Hadoop

  Leverage state of the art NLP Algorithms for detection of personal health information (PHI) entities within free text comments to automatically de-identify natural language

  Modularize the entity-based feature engineering code base on Hadoop to leverage big data technologies such as Pyspark and Spark SQL.

Qualifications

• Candidates working towards a Master’s degrees or a PhD in quantitative disciplines such as Data Science, Statistics, Applied Mathematics, Computer Science, Bioinformatics, Computational Linguistics or related quantitative disciplines
• Excellent ability to query large datasets using ANSI SQL/HIVE SQL and working with relational databases
• Proficient programming skills either in SAS, R, or Python
• Proficient in Basic Probability and Statistics
• Preference given to students with 3.0 GPA or above with demonstrated proficiency in quantitative subjects

Additional Experience Required

• Proficient with one or more quantitative data analysis languages such as R, Python
• Demonstrated coursework / real world application of analytical methods such as Regression, Naïve-Bayes, Decision trees, experimental designs, support vector machines, machine learning and text mining, Natural Language Processing
• Proficiency with relational database concepts and SQL preferred
• Proficiency in data manipulation, cleansing and interpretation
• Experience working in distributed computing and Big Data Technologies like Hive, Spark, Scala, HDFS
• Experience with visualization tools like Tableau, Shiny, ggplot, Matplotlib
• Experience with Microsoft Office Suite

Additional Information

• Location: This in an in-office internship.  Applicants should be prepared to be aligned to one of the following locations:
  • 4600 North Hanley, St. Louis, MO 63134
  • 115 Tabor Road, Morris Plains, NJ 07950
  • 11501 Alterra Pkwy, Austin, TX 78758

• Work Authorization: One goal of this internship program is to prepare and identify qualified candidates for roles with The Cigna Group post-graduation. Therefore, this temporary internship is open only to individuals who are eligible for employment in the United States and who would not require visa sponsorship now or in the future.

• Schedule: You must be available to work 40 hours/week for 12 consecutive weeks beginning May 19, 2025.  Working hours are Monday – Friday

• Compensation: For this position, we anticipate offering an hourly rate between $40.00 and $43.00 an hour depending on relevant factors, including major and year of study.

About The Cigna Group

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 require reasonable accommodation in completing the online application process, please email: SeeYourself@cigna.com for support. Do not email SeeYourself@cigna.com for an update on your application or to provide your resume as you will not receive a response.

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.