Data Scientist Intern – Express Scripts-Cigna

Website Cigna


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. Cigna’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
The Data Science Internship is an opportunity to be part of the most exciting company in healthcare, making medicine smarter and more affordable using data science. 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.
During this internship, the intern will utilize machine learning for developing the next generation of predictive models for targeted business solutions, support the team in the application of Text Mining to mine VoC data, and develop supervised/unsupervised algorithms for making business processes efficient.


  • Must be working towards Masters Degrees or a Ph.D. in quantitative disciplines such as Statistics, Applied Mathematics, Computer Science, Econometrics, Finance, Engineering, Operations Research, Bioinformatics, Information Systems, Computational Linguistics or related quantitative disciplines or other similar degrees
  • Excellent ability to query large datasets using ANSI SQL and working with relational databases
  • Proficient programming skills either in SAS, R, or Python
  • Proficient in Basic Probability and Statistics
  • Preference is given to students with a 3.0 GPA or above with demonstrated proficiency in quantitative subjects.

Experience Desired

  • Proficiency 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, and Natural Language Processing
  • Proficiency with relational database concepts and SQL preferred
  • Proficiency in data manipulation, cleansing, and interpretation
  • Knowledge of Big Data Technologies like Hive, Spark, Scala, HDFS
  • Experience with visualization tools like Tableau, Shiny, ggplot, Matplotlib
  • Proficiency with Microsoft Office Suite

The following competencies/behaviors will be expected for incumbents in this position:

  • Motivated self-starter
  • Excellent verbal and written communication skills
  • Attention to detail with excellent analytical skills
  • Able to quickly pick up new ideas and new technologies
  • Some Project Management knowledge helpful but not mandatory

About Cigna

Cigna Corporation (NYSE: CI) is a global health service company dedicated to improving the health, well-being and peace of mind of those we serve. We offer an integrated suite of health services through Cigna, Express Scripts, and our affiliates including medical, dental, behavioral health, pharmacy, vision, supplemental benefits, and other related products. Together, with our 74,000 employees worldwide, we aspire to transform health services, making them more affordable and accessible to millions. Through our unmatched expertise, bold action, fresh ideas and an unwavering commitment to patient-centered care, we are a force of health services innovation.
When you work with Cigna, you’ll enjoy meaningful career experiences that enrich people’s lives while working together to make the world a healthier place. What difference will you make? To see our culture in action, search #TeamCigna on Instagram.
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.
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