Corporate Medical Job at J&J: Turn Healthcare Data Into Impact | Apply Now!

Johnson & Johnson is a global healthcare organisation focused on developing innovative medicines, medical technologies and healthcare solutions. With operations spanning multiple areas of healthcare, the organisation brings together scientific expertise, technology and patient-focused innovation to address complex health challenges. Its global teams work across research, data science, epidemiology and healthcare technology.

Location: Hyderabad, India
Function: Data Analytics & Computational Sciences, Epidemiology
Work Pattern: Hybrid
Travel: Up to 10% domestic/international

About the role

The Manager, Observational Health Data Analytics, Epidemiology role offers an opportunity to lead complex observational studies using large-scale healthcare datasets. The selected professional will be part of the Global Epidemiology team and will lead the design and execution of observational research using real-world healthcare data. This position requires substantial experience in epidemiology, statistical programming, healthcare datasets and research methodology.

Responsibilities

• Collaborate with OHDA, Global Epidemiology and cross-functional teams.
• Lead the design and delivery of observational analyses.
• Support clinical characterization and population-level effect estimation.
• Contribute to patient-level prediction research.
• Develop study protocols, analysis plans and other study documents.
• Guide analytical execution from study design through completion.
• Conduct complex analyses using statistical programming and standardized tools.
• Work with internal and external observational healthcare data resources.
• Improve research methods, analytical processes and scientific best practices.
• Support reliable and reproducible real-world evidence generation.
• Contribute to software and analytical tools for scalable observational research.
• Evaluate healthcare datasets for fitness-for-use.
• Provide technical and scientific leadership for epidemiological data environments.
• Mentor junior team members.
• Contribute to reports, presentations and other scientific deliverables.

Requirements

Candidates must meet one of the following educational and experience pathways:

• MD / PhD Route: MD or PhD with at least 6+ years of epidemiology programming or related research experience, and at least 8+ years of epidemiology or related healthcare research experience.

Candidates should also have:

• At least 4 years of statistical programming using R and/or database programming using SQL.
• At least 2 years of experience working with large healthcare datasets, including claims or electronic health records.
• At least 2 years of healthcare industry experience, such as pharmaceutical, payer, provider, health system, CRO or related research environments.
• Experience with administrative claims data and/or electronic health or medical record data.
• Experience with data visualization or reporting tools such as R Shiny and ggplot2.
• Experience developing epidemiology study documents, including protocols and study reports.
• Strong quantitative data analysis and interpretation abilities.
• Excellent written and verbal communication skills.
• Fluency in English.
• Ability to travel up to 10% domestically and internationally when required.

Preferred Qualifications

• Leadership experience in epidemiology or real-world evidence research.
• Experience with OHDSI and/or OMOP Common Data Model.
• Knowledge of ICD, NDC, SNOMED, MedDRA, LOINC and CPT medical terminologies.
• Experience in pharmaceutical, medical device, diagnostics or related healthcare research.
• Scientific publications, posters, presentations or technical reports.
• Familiarity with AI-enabled analytics or intelligent automation in research workflows.

Skills

• Advanced epidemiological research skills
• Strong statistical programming capabilities
• Proficiency in R and/or SQL
• Experience handling large-scale healthcare datasets
• Knowledge of observational study methodologies
• Real-world evidence research experience
• Strong data interpretation and analytical skills
• Experience developing research protocols and analysis plans
• Understanding of healthcare data standards and medical terminologies
• Strong scientific writing and presentation abilities
• Cross-functional collaboration skills
• Technical leadership and mentoring abilities
• Ability to work independently on complex research projects