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Principal Scientist, Data Science

At Johnson & Johnson,we believe health is everything.

Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com .

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world.

We provide an inclusive work environment where each person is considered as an individual.

At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:
Data Analytics & Computational Sciences

Job Sub Function:
Data Science

Job Category:
Scientific/Technology

All Job Posting Locations:
New Brunswick, New Jersey, United States of America

Job Description:

Employer: Janssen Research & Development, LLC

Job Title: Principal Scientist, Data Science

Job Code: A011.4028.11

Job Location: New Brunswick, NJ

Job Type: Full-Time

Rate of Pay: $169,541 - $171,000/year

Job Duties: 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 and delivering Real-World Data (RWD) methodologies to mitigate observed and unobserved bias and confounding in the execution of comparative effectiveness analyses, time-to-event analyses, external control arm studies, synthetic and hybrid control arm studies, observational and prospective study designs, burden of disease estimation, cohort selection and characterization, incidence/prevalence studies, non-inferiority studies, development of risk stratification algorithms, and creation of disease severity indices.

Act as a co-participant in cross-functional collaborations with external companies and internal scientific and data science teams.

Shape internal and external collaborations and define the scope of research questions.

Extract insights from large observational patient databases (e.g., electronic health records, claims, registries) to inform health outcomes and support drug development.

Clearly articulate complex technical methods and results to diverse audiences and stakeholders to support decision-making.

Mentor junior team members in applying appropriate methods for real-world data analysis.

Requirements: Employer will accept a 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 Scie...




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