Janssen Research & Development (“JRD”), a Johnson & Johnson company, is recruiting for a Scientist, Data Science, Real-World Evidence (“RWE”). The primary location for this position is flexible – either; Titusville, NJ; Raritan, NJ; Spring House, PA; Cambridge, MA; New York City, NY; San Diego, CA; South San Francisco, CA; remote may also be considered with up to 10% travel.

Janssen develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, cardiovascular and metabolic disorders, immunology, pulmonary hypertension, neuroscience, and infectious disease. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about Janssen, one of the Pharmaceutical Companies of Johnson & Johnson, visit https://www.janssen.com/us/.

The R&D Data Science Analytics & Insights team within Janssen develops innovative solutions leveraging a variety of different data sources across multiple disease areas. We are looking for outstanding scientists whose responsibilities include:

Closely partner with the Data Science Portfolio Management and Therapeutic Area teams to execute on the priorities, building a roadmap to deliver the projects from data feasibility to final presentation to senior cross-functional leaders
Conceive, develop, and implement analytics solutions to high-priority scientific problems
Lead and implement user cases 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 control arm studies, hybrid control arm studies, observational and prospective study designs, burden of disease estimation, cohort selection and characterization, incidence/prevalence studies, non-inferiority studies, and the development of algorithms for risk stratification, and creating disease severity indices
Coparticipant in cross-functional collaborations with external companies and internal scientific and data science teams
Shape internal/external collaborations and define the scope of research questions
Extract insight from large, observational patient databases (e.g., electronic health records, claims, registry, etc.) to health outcomes and drive drug development
Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making
Mentor junior team members in the application of appropriate methods for real-world data
Qualifications
A Ph.D. or a master’s degree (with at least 3 years of relevant within a start-up, technology, biopharma, or healthcare industry) in a quantitative discipline (e.g., epidemiology, statistics, biostatistics, health economics, biomedical informatics, computer science, artificial intelligence, or similar)
Experience with exploratory data analysis, statistical modeling, causal inference methods to mitigate observed and residual confounding (propensity score matching/ weighting, instrumental variables, state transition models)
Experience querying, cleaning, and integrating data to build cohorts from RWD (Real Word Data) sources
Experience with medical coding and disease ontologies
Proficiency with one or more programming languages such as Python, R, SAS, SQL, C++, or Java
Passionate about leveraging data to drive scientific innovation

Preferred qualifications:
Hands-on technical data analysis and modeling experience (across roles)
Experience building external/synthetic control arms for clinical trials
Familiarity with OMOP CDM (Common Data Model)
Familiarity with and exposure to drug discovery and clinical development processes
Experience working closely with healthcare professionals
Experience with meaningful disease biology in cancer, immunology, neuroscience, cardiovascular, or infectious disease
Experience with Natural Language Processing
Experience with supervised and unsupervised machine learning algorithms
Ability to effectively communicate technical work to a wide audience

Thriving on a diverse company culture and celebrating the uniqueness of our employees, we are committed to inclusion. We are proud to be an equal opportunity employer.

Johnson & Johnson is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

Working with Johnson & Johnson can change everything. Including YOU.

The anticipated base pay range for this position is $101,500 to $163,300.

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