Real World Data Analyst II
Bristol Myers Squibb (company site, opens in a new tab)5+ yrsHyderabadOn-siteDirect career pageEst. 14–26 LPA
Posted 16d ago
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at Bristol Myers Squibb
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Bristol Myers Squibb you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Collaborate with cross-functional teams to deliver real-world data (RWD) analysis solutions on time and within budget for R&D functions.
- Identify, preprocess, and analyze RWD from multiple healthcare sources to generate insights addressing research questions and business objectives.
- Oversee and conduct observational and comparative effectiveness studies, communicate findings to stakeholders, and ensure compliance with regulatory guidelines related to RWD analysis.
Minimum Requirements
- Bachelor's or Master's degree in Biostatistics, Epidemiology, Health Informatics, or related field.
- Minimum 5 years of experience in real-world data analysis within biopharma or healthcare industry.
- Proficiency with Python, R or SAS, Domino platform, and visualization tools like Tableau or Power BI, including expertise in data preprocessing and understanding of RWD pipelines.
- Knowledge of regulatory requirements for RWD use (e.g., FDA's Real-World Evidence Program) and full-time position based in Hyderabad, India.
Ideal Candidate Profile
- Experienced in biopharma real-world data environments with strong domain knowledge and functional expertise in RWD platforms and analysis.
- Comfortable working with both structured and unstructured healthcare data and capable of guiding junior team members and stakeholders.
- Operates effectively in cross-functional teams managing multiple projects, focused on automation, cost optimization, and continuous learning of new tools and AI use cases.