Manager, Observational Health Data Analytics - Basel, CH

CH024 ACT Allschwil, Switzerland

Johnson & Johnson

Johnson &Johnsonis a leading wholesale broker with commercial and personal lines expertise.

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At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions 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 https://www.jnj.com

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Epidemiology

Job Category:

Scientific/Technology

All Job Posting Locations:

Allschwil, Basel-Country, Switzerland

Job Description:

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.
 

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
 

Learn more at https://www.jnj.com/innovative-medicine
 

Johnson & Johnson Innovative Medicine is recruiting for a Manager, Observational Health Data Analytics position in the Global Epidemiology Organization (GEO).  This is a Hybrid role available in Basel, Switzerland.

Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s):
 

Switzerland - Requisition Number: R-016763

Belgium - Requisition Number: R-016766
United States of America - Requisition Number: R-015652
 

This position is a member of the Observational Health Data Analytics (OHDA) team within GEO. OHDA’s mission is to improve the lives of individuals and quality of healthcare by efficiently generating real-world evidence from the world’s observational health data, transparently disseminating evidence-based insights to real-world decision-makers, and objectively advancing the science and technology behind reliable, reproducible real-world analytics.
 

The OHDA team collaborates with GEO and the broader Johnson & Johnson organization generating and disseminating real-world evidence about disease, health service utilization, and the effects of medical products through the analysis of healthcare data. OHDA collaborates with the broader international research community to establish and promote best practices in the appropriate use of observational data by conducting methodological research, developing standardized analytic tools, and demonstrating successful applications to important clinical questions.
 

Primary responsibilities:

  • Work closely with colleagues within GEO.
  • Contribute to the successful delivery of observational analyses for clinical characterization, population-level effect estimation, and patient-level prediction to meet the needs of Johnon & Johnson’s scientific and business functions.
  • Contribute to the design of observational database analysis, including authoring protocol and analysis plans.
  • Contribute to the execution of observational database analyses by using standardized analytical tools and writing statistical programs against internal and external observational data resources.
  • Contribute to innovating, evaluating, and establishing scientific best practices around the design and conduct of observational analysis and accompanying processes to ensure the reliability of real-world evidence.
  •  Contribute to the design and development of software and analytical tools that encode scientific best practices into solutions that enable real-world evidence generation and dissemination.
  • Contribute to the development and evolution of scientific and industry standards for observational data harmonization, ensuring their appropriate application across the Johnson & Johnson real-world data ecosystem, and leading the evaluation and characterization of observational data for their fitness-for-use to address clinical questions from across the organization.
  • Contribute to technical support for the data and analysis infrastructure and provide scientific support for conducting observational research in collaboration with epidemiologists and product teams.
  • Be able to work in a matrix environment, engage with external teams and contribute to scientific contributions.


Qualifications:

  • We require you to have an undergraduate degree in biostatistics, public health, epidemiology, informatics, computer science, or related disciplines. A graduate degree (Masters or PhD) is preferred.
  • At least 2 years of experience in statistical programming (R), or database programming (SQL).
  • At least 1 year of programming against large healthcare data sets.
  • At least 1 year of relevant prior work experience in the healthcare industry within a pharmaceutical company, insurer, or within a health system.
  • At least 1 year of epidemiology research experience is preferred.
  • Experience with the statistical analysis and management of administrative claims datasets or electronic health/medical records.
  • Knowledge of medical terminologies (ICD, NDC, SNOMED, MedDRA, LOINC, CPT) is preferred.
  • A record of accomplishment of authoring scientific communications (peer-reviewed publications, poster or oral presentations at conferences, technical reports) is preferred.
  • This position currently allows for the option to follow a hybrid schedule of 3 days per week working on one of the site locations listed in this posting and 2 days per week working remotely.  (No fully remote option available.) May require up to approximately 10% travel.

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Tags: Biostatistics Computer Science Data Analytics LOINC Pharma PhD R Research SNOMED SQL Statistics

Perks/benefits: Conferences

Regions: Remote/Anywhere Europe
Country: Switzerland

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