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Statistical Programming Intern

0-2 years
Not Disclosed
10 Dec. 18, 2025
Job Description
Job Type: Full Time Hybrid Education: B.Sc/M.Sc/M.Pharma/B.Pharma/Life Sciences Skills: Causality Assessment, Clinical SAS Programming, Communication Skills, CPC Certified, GCP guidelines, ICD-10 CM Codes, CPT-Codes, HCPCS Codes, ICD-10 CM, CPT, HCPCS Coding, ICH guidelines, ICSR Case Processing, Interpersonal Skill, Labelling Assessment, MedDRA Coding, Medical Billing, Medical Coding, Medical Terminology, Narrative Writing, Research & Development, Technical Skill, Triage of ICSRs, WHO DD Coding

Statistical Programming Intern | Princeton, NJ

Job ID: R14680
Category: Research & Discovery
Location: Princeton, New Jersey, United States
Job Type: Internship (June – August 2026, Hybrid)


About Genmab

Genmab is a leading international biotechnology company dedicated to advancing patient care through innovative antibody therapeutics. With more than 25 years of expertise, the company has developed next-generation antibody platforms, including bispecific T-cell engagers, antibody-drug conjugates, and immune checkpoint modulators.

Headquartered in Copenhagen, Denmark, Genmab operates across North America, Europe, and Asia-Pacific, shaping the future of oncology and serious disease treatment with Knock-Your-Socks-Off (KYSO®) antibody medicines.

Learn more at www.genmab.com.


Internship Overview

The Statistical Programming Internship offers a 10-week summer program that provides hands-on experience in clinical research programming within Genmab’s drug development pipeline. Interns will contribute to data mapping (SDTM), creation and quality control of analysis datasets (ADaM), statistical reporting (TLF), tool development, and cross-functional collaboration.

This hybrid internship is based in Princeton, NJ, with 3 days onsite and 2 days remote per week.


Key Responsibilities

Technical Exposure

  • Gain hands-on experience with programming tools including SAS, R, and Python.

  • Support production of analysis datasets, tables, figures, and listings by writing, testing, and validating programs.

  • Develop data visualizations and automation tools to streamline programming tasks.

Clinical Research Integration

  • Learn industry standards, best practices, and regulatory requirements for Clinical and Statistical Programming.

  • Support reporting and visualization of clinical trial data.

  • Gain familiarity with computing environments, applications, and tools used in clinical research programming.

Professional Development

  • Participate in weekly mentorship meetings with programming leads.

  • Engage in cross-functional collaboration with Biostatistics and Data Management teams.

Capstone Project

  • Complete a capstone project based on a real programming assignment, e.g., automation of data checks for FDA submissions or testing code libraries.

  • Present project outcomes to the Extended Programming Leadership Team, demonstrating skills, insights, and potential for future full-time opportunities.


Required Qualifications

  • Students in their second year of a Master’s degree in Statistics, Mathematics, Computer Science, Bioinformatics, Data Science, or related fields. (Expected Graduation: Dec 2026 or May 2027)

  • Interest in clinical research.

  • Basic understanding of clinical and statistical programming.

  • Academic experience with SAS, R, or Python.


Preferred Qualifications

  • Advanced experience with SAS, R, or Python.

  • Familiarity with clinical trial datasets, statistical reporting, and automation techniques.


Internship Benefits

  • Hands-on experience in clinical data programming and statistical analysis.

  • Exposure to cross-functional and global collaboration.

  • Development of technical, analytical, and problem-solving skills relevant to clinical research.

  • Opportunity to contribute to real-world projects impacting Genmab’s oncology pipeline.


About You

  • Passionate about clinical research and data programming.

  • Collaborative, proactive, and solution-oriented.

  • Adaptable in a fast-paced, dynamic environment.

  • Committed to precision, quality, and continuous learning.