Jobs / United States / Cigna Health And Life Insurance Company
Analytics Leadership Development Program (ALDP) Summer Internship
Cigna Health And Life Insurance Company · 🇺🇸 CT, Bloomfield, 900 Cottage Grove Rd Wilde Bldg
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 14 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest May 2026) — the step every H-1B hire needs first. USCIS also records 30 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Cigna Health And Life Insurance Company paid sponsored hires in similar roles1 certified filing for “Operations Director (Program Director)” (Information Technology Project Managers) in VA: $190k–$190k, median $190k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Cigna Health And Life Insurance Company
The US Department of Labor certified 14 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest May 2026) — the step every H-1B hire needs first. USCIS also records 30 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Cigna Health And Life Insurance Company →
About the role
Analytics Leadership Development Program (ALDP) – Summer 2027 Intern The Cigna Group, together with its wholly owned subsidiary Evernorth, is seeking highly motivated graduate students to join the Analytics Leadership Development Program (ALDP) as Summer 2027 Interns. This internship is designed for candidates with a strong foundation in analytics and data science, meaningful hands-on experience, and an interest in developing as future analytics leaders. The ALDP offers an immersive learning experience that combines real-world analytical work with business strategy, professional development, and leadership exposure, preparing interns for full-time analytics roles following graduation. At Evernorth, data and analytics play a critical role in improving health outcomes, advancing equity, and driving affordability across the healthcare system. ALDP interns contribute to impactful work that supports smarter, data-driven healthcare solutions while building both technical and leadership capabilities. Internship Experience As an ALDP Intern, you will be embedded within an analytics team and work on real business problems that strengthen your analytical thinking, technical skills, and ability to communicate insights. Interns are supported by experienced leaders, mentors, and peers throughout the program. Example project areas may include: • Developing predictive models to identify customers who may benefit from targeted clinical or support programs • Applying machine learning techniques to segment populations and enable personalized engagement strategies • Analyzing drivers of medical cost trends and recommending data-driven mitigation strategies • Measuring the impact of business initiatives using experimental or quasi-experimental methods • Modeling the financial impact of changes to provider contracts or healthcare delivery models Required Qualifications • Currently pursuing a Master’s degree in a quantitative field such as Data Science, Statistics, Mathematics, Analytics, or a closely related discipline • Prior hands‑on experience gained through internships, co‑ops, research assistantships, paid employment, or applied academic projects involving analytics, data science, statistics, or quantitative modeling (experience may include coursework, capstone projects, research labs, consulting or contract work, or part‑time roles) • Experience applying analytical methods, including: • Programming in Python or R • Building, evaluating, or interpreting analytical or statistical models (e.g., linear or logistic regression, decision trees, or introductory machine learning models) • Applying statistical concepts such as hypothesis testing, experimental design, or A/B testing • Experience working with relational data and writing SQL queries to extract, manipulate, and analyze data • Foundational understanding of machine learning concepts, including supervised vs. unsupervised learning, feature engineering, and model evaluation • Strong problem‑solving and critical‑thinking skills, with the ability to structure ambiguous problems and develop data‑driven approaches • Demonstrated interest in leadership development, shown through academic, professional, teaching assistant, research, or extracurricular experiences • Ability to clearly communicate analytical insights to both technical and non‑technical audiences • Ability to work effectively in a collaborative, team‑based environment, incorporating feedback and diverse perspectives • Availability to work 40 hours per week for the full 12‑week internship program Preferred Qualifications • Exposure to machine learning tools or frameworks through graduate‑level coursework, projects, or internships (e.g., scikit‑learn, TensorFlow, PyTorch, or large languag