Statistical Programmer Intern - Hybrid Data Analysis

MSD Malaysia

Rahway (NJ)

Hybrid

USD 40,000 - 111,000

Full time

5 days ago
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Benefits offered by this job

Hybrid work model
Intern/Co-op (Fixed Term)

Job summary

MSD Malaysia is offering the Future Talent Program internship in the BARDS division. Interns will develop and deliver statistical analyses and reporting under supervision, contributing to trials and regulatory discussions.

The program runs 10–12 weeks in a hybrid work environment starting June 2027, with opportunities to grow within our global health portfolio. Candidates must be enrolled in relevant MS programs, demonstrate data analysis and programming skills, and show collaboration and strong

Qualifications

  • Students must be enrolled and have completed at least two semesters of work toward an MS by May 2027.
  • Commit to full-time hybrid employment for 10–12 weeks starting June 2027.
  • Data analysis experience and programming skills are required.
  • Willingness to learn new programming languages and techniques.
  • Ability to collaborate on a team and communicate effectively.

Responsibilities

  • Develop and execute statistical analysis and reporting deliverables under guidance of a senior programmer.
  • Support analysis datasets, tables, listings, and graphics across BARDS activities.
  • Collaborate with scientists and health authorities to inform decision making.

Skills

Data analysis
Programming skills
Willingness to learn
Team collaboration
Oral and written communication

Education

MS in Computer or Data Science
Statistics
Applied Mathematics / Life Sciences / Engineering

Job description

MSD Malaysia is offering the Future Talent Program internship in the BARDS division. Interns will develop and deliver statistical analyses and reporting under supervision, contributing to trials and regulatory discussions.

The program runs 10–12 weeks in a hybrid work environment starting June 2027, with opportunities to grow within our global health portfolio. Candidates must be enrolled in relevant MS programs, demonstrate data analysis and programming skills, and show collaboration and strong

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