IDAR Student Placement: Clinical & Statistical Programming

Johnson & Johnson Co.; Maidenhead; On-site; GBP 11,000 - 16,000; Part time

Job summary

Johnson & Johnson is offering a 12-month Integrated Data Analytics and Reporting (IDAR) placement in Clinical and Statistical Programming. You will gain hands-on experience with data integration, automation, and clinical insights while collaborating with experienced teams.

The role emphasizes applying AI programming to develop statistical solutions and support trial analyses, with opportunities to work on innovative tools and documentation across disease areas.

Qualifications

• Successful completion of the first two years of a degree course.
• A minimum of a 2:1 achieved in the first year.
• Mathematical, Life Sciences, Computer Science, Data Science and related degrees preferred.

Responsibilities

• Work with Clinical & Statistical Programming counterparts applying analyses in an array of disease areas.
• Conduct research to identify innovative solutions that can be applied to our business processes.
• Collaborate with team members to design and develop solutions using SAS, R, Python, RPA, Power Automate and other tools.
• Create and maintain documentation for solutions.
• Stay up to date with emerging technologies and trends.

Skills

Analytical thinking

Problem solving

Communication skills

Teamwork

Independent work

Education

First two years of degree completed

2:1 in first year

Mathematical, Life Sciences, Computer Science or Data Science degree preferred

Tools

SAS

R

Python

RPA

Power Automate

Job description

Johnson & Johnson is offering a 12-month Integrated Data Analytics and Reporting (IDAR) placement in Clinical and Statistical Programming. You will gain hands-on experience with data integration, automation, and clinical insights while collaborating with experienced teams.

The role emphasizes applying AI programming to develop statistical solutions and support trial analyses, with opportunities to work on innovative tools and documentation across disease areas.