AI SCORE 8.5

Intern - Real-World Data Analytics (Remote)

$50K–$60K/year

About the Role

Join Labcorp's 2026 Global Internship Program as a Real-World Data Analytics Intern to gain hands-on experience in healthcare innovation while supporting our mission to improve health. This is a unique opportunity to work remotely as a Real-World Data Analytics Intern, where you will contribute to impactful projects related to Real-World Data analysis.

What You'll Do

  • Engage in a 12-week paid internship from May 18, 2026, to August 7, 2026, focusing on real-world data analytics.
  • Work on projects that enhance healthcare outcomes through data analysis.
  • Gain exposure to Labcorp’s global business and culture, participating in workshops, panels, and networking events.
  • Present your findings to Senior Leadership, honing your presentation skills and gaining valuable feedback.
  • Build professional connections with peers and industry professionals, fostering a network that will benefit your career.

Requirements

  • Pursuing a degree in Data Science, Bioinformatics, Computer Science, Health Informatics, or a related field.
  • Familiarity with oncology, biostatistics, and health data management is preferred.
  • Proficiency in programming languages such as Python, R, or SQL.
  • Experience with databases like MySQL, PostgreSQL, and data visualization tools.
  • Understanding of statistical methods in health data analysis.
  • Strong problem-solving and analytical skills, with a meticulous approach to data accuracy and integrity.
  • Ability to present findings clearly to diverse audiences, showcasing your communication skills.
  • Interest in oncology and healthcare improvements, demonstrating your passion for the field.

Nice to Have

  • Experience working in teams with a positive attitude.
  • Previous internship experience in data analytics or a related field.
  • Knowledge of healthcare data regulations and compliance.

What We Offer

  • Comprehensive benefits for employees working 20+ hours per week, including Medical, Dental, Vision, Life insurance, and 401(k) plans.
  • Paid Time Off (PTO) or Flexible Time Off (FTO) to ensure work-life balance.
  • Tuition Reimbursement and Employee Stock Purchase Plan to support your professional growth.
  • An inclusive culture and engagement with employee resource groups, fostering a supportive work environment.
  • Relocation assistance for qualified candidates, making this a great opportunity for those willing to move.
Why This Job8.5 of 10

This internship offers a unique opportunity to gain hands-on experience in data analytics within the healthcare sector. With comprehensive benefits and a supportive work environment, it's an excellent stepping stone for your career.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

Proficiency in Python and SQL for data manipulation and analysis, with experience using libraries like Pandas and NumPy, essential for processing large datasets in healthcare.

Strong analytical mindset with a focus on biostatistics and health data management, allowing for effective interpretation of data trends and patterns in a remote work environment.

Self-motivated learner with the ability to work independently and manage time effectively while collaborating with remote teams, ensuring project milestones are met during the internship.

Learning Resources

Python for Data Science Handbookguide

Career Path

Intern - Real-World Data Analytics(Now)Data Analyst(1-2 years)Senior Data Analyst or Data Scientist(3-5 years)

Market Overview

Market Size 2024
$15.5B
Annual Growth
24.3%
AI Adoption
60%
Investment
+40%
Labour Demand
+35%
Avg Salary
$75K

Skills & Requirements

Required
PythonRSQL
Growing in Demand
Machine LearningData EngineeringCloud Computing
Declining
SASSPSS

Domain Trends

Increased Demand for Health Data Analytics
The global health data analytics market is projected to grow by 28% annually, driven by the need for actionable insights in healthcare.
Integration of AI in Data Analytics
60% of companies are investing in AI tools for data analytics, enhancing predictive capabilities and operational efficiency.
Shift Towards Open-Source Tools
Over 70% of data professionals are now using open-source tools like Python and R, leading to a decline in proprietary software usage.

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