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About This Role
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 [email protected] 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.
Salary Context
This $72K-$89K range is in the lower quartile for Data Scientist roles in our dataset (median: $167K across 172 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 9,653 AI roles we're tracking, Data Scientist positions make up 5% of the market. At The Cigna Group, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $190,000 based on 1,406 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $110,408. This role's midpoint ($81K) sits 57% below the category median. Disclosed range: $72K to $89K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
The Cigna Group AI Hiring
The Cigna Group has 5 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span Bloomfield, CT, US, Orlando, FL, US, Morris Plains, NJ, US. Compensation range: $89K - $219K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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