Principal Data Scientist, Real-World Health Analytics

Johnson & Johnson Innovative Medicine; New Brunswick (NJ); On-site; USD 170,000 - 171,000; Full time

Benefits offered by this job

Vacation 120 hours per calendar year

Sick time 40 hours per calendar year

Holiday pay 13 days per calendar year

Parental Leave 480 hours per year

Bereavement Leave 240 hours per year

Caregiver Leave 80 hours per year

Volunteer Leave 32 hours per year

Military Spouse Time-Off 80 hours per年

Medical, dental, vision benefits

Job summary

Johnson & Johnson Innovative Medicine in New Jersey is seeking a Principal Scientist, Data Science to lead analytics initiatives across R&D Data Science and Digital Health.

The role focuses on designing and implementing analytics solutions for high-priority scientific problems, mentoring junior staff, and shaping collaborations to support drug development with real-world data techniques.

Qualifications

• Master's degree in Epidemiology, Biostatistics, Statistics or related quantitative field and 4 years of experience in the job offered or in a Principal Scientist, Data Science-related occupation.

Responsibilities

• Closely partner with R&D Data Science and Digital Health, as well as multidisciplinary teams within J&J Innovative Medicine, to execute priorities and build a roadmap for delivering projects from data feasibility to final presentation to senior cross-functional leaders.
• Conceive, develop, and implement analytics solutions for high-priority scientific problems.
• Lead and implement use cases by adapting Real-World Data methodologies to mitigate bias and confounding in comparative effectiveness analyses, time-to-event analyses, external control arm studies, and observational designs.

Education

Master's degree in Epidemiology, Biostatistics, Statistics or related quantitative field

Job description

Johnson & Johnson Innovative Medicine in New Jersey is seeking a Principal Scientist, Data Science to lead analytics initiatives across R&D Data Science and Digital Health.

The role focuses on designing and implementing analytics solutions for high-priority scientific problems, mentoring junior staff, and shaping collaborations to support drug development with real-world data techniques.