The Cigna Group is looking to solve real-world challenges in healthcare by leveraging technology, particularly in the area of data and analytics engineering, to improve health outcomes and drive business decisions.
Requirements
Familiarity with programming languages and tools such as Python, JavaScript, SQL, R, React, Power BI, AWS.
Relevant skills like Prompt Engineering or Tableau.
AI-Native Mindset: Naturally integrates AI tools and techniques into data workflows—leveraging machine learning, generative AI, and automation to accelerate analysis, enhance predictions, and improve data-driven decision-making.
Academic coursework, projects, research, or internships that demonstrate hands-on experience with data modeling, analytics, machine learning, or business intelligence.
Experience with cloud platforms, big data tools, and predictive models.
Familiarity with data architecture, engineering, and visualization.
Knowledge of machine learning, generative AI, and automation.
Responsibilities
Work within the Data & Analytics Engineering track, contributing to the design, development, and optimization of data pipelines, platforms, and analytical tools.
Gain hands-on experience transforming raw data into actionable insights, deepening skills in data architecture, engineering, and visualization while helping drive data-informed decision-making across The Cigna Group.
Design scalable pipelines, model data for clarity, and apply advanced analytics to solve real-world problems.
Work with big data tools, cloud platforms, and predictive models to help shape smarter decisions across the business.
Participate in structured learning through both core and track-specific curriculum, including technical training, leadership development, and exposure to the business.
Engage with peers, mentors, and cross-functional partners through community-building activities and collaborative initiatives.
Build meaningful relationships across the organization through networking events, mentorship, cross-functional collaboration, or informal peer engagement.
Other
Full time candidates must have completed a bachelor’s or master’s degree in a technical program at the time of hire.
Preferred degrees include Computer Science, Data Science, Machine Learning, and Artificial Intelligence.
Leadership or involvement in student organizations, analytics clubs, or technical competitions (e.g., data hackathons, Kaggle challenges, case competitions) that showcase teamwork, creativity, and problem-solving.
A cumulative GPA of 3.3 or higher is preferred.
Must be available to work a 40-hour work week beginning July 13, 2026.
