Data Scientist Intern- Master's Program (Hybrid: NJ, TX, or MO)

The Cigna Group, through Evernorth Health Services, provides healthcare services and is committed to improving health and vitality. The Data Scientist Intern will develop and evaluate predictive, machine learning, NLP, and generative AI solutions for healthcare and business challenges, translate complex datasets into actionable insights, build data pipelines and models, and communicate findings to stakeholders and leadership.

What you'll do:

• 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

What they're looking for:

• 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
• 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

Benefits:

• Hybrid schedule, spending three days per week in the office and two days working remotely
• Professional development and networking
• Direct engagement with senior data science leaders and clinical stakeholders