Senior Manager, Real World Evidence Analyst - Starszy Manager ds. Analityki Rzeczywistych Dowodów (Real World Evidence - RWE)
Bristol-Myers Squibb
Senior Manager, Real World Evidence Analyst - Starszy Manager ds. Analityki Rzeczywistych Dowodów (Real World Evidence - RWE)
Job Description
Curate and assess the quality of real-world data (RWD) assets to ensure their suitability and understanding for intended use. Design and implement data pipelines to transform raw RWD into datasets ready for analysis. Collaborate with cross-functional teams—including Biostatistics, Data Science, HEOR, Epidemiology/Safety, Clinical, and IT—to define data requirements and analytical strategies. Conduct exploratory data analyses, identify patient cohorts, and perform data summary analytics to support real-world evidence (RWE) generation. Participate in the design of RWE studies, including the development of methodologies, data analysis, interpretation, and reporting of study results. Author or review study documents such as protocols, statistical analysis plans, study reports, publications, and study-level specifications. Develop and maintain documentation detailing data sources, transformations, and analytical methods. Ensure all work complies with data governance, privacy, and regulatory standards. Stay up to date with industry and regulatory trends, tools, and best practices in RWD/RWE analytics. Continually expand technical knowledge of statistical considerations in real-world evidence generation to ensure high-quality study design and analysis. Enhance understanding of the drug development process, as well as regulatory and commercial requirements. Supporting People with Disabilities Master's or PhD in Epidemiology, Biostatistics, Data Science, Health Informatics, or a related field. 3+ years of experience working with real-world healthcare data (claims, EMR, registries, etc.). 2+ years of experience in pharmaceutical industry (e.g. Pharma, CRO, Biotech) and clinical trials. Proficiency in SAS, R, Python, or similar tools for data manipulation and analysis. AI/ML knowledge is a plus. Good verbal and written communication skills in English Good understanding of industry RWD vendor database. Experience with RWD data curation, engineering, exploration, and quality control in large-scale datasets. RWD trial design and analysis experience Ability to communicate complex real-world data concepts to non-technical stakeholders. Ability to work successfully within cross-functional teams Ability to organize multiple work assignments and establish priorities Strong understanding of healthcare industry regulatory compliant data standards. Good understanding of regulatory requirements & clinical trial design is preferred.
Key Responsibilities
- Curate and assess the quality of real-world data (RWD) assets to ensure their suitability and understanding for intended use
- Design and implement data pipelines to transform raw RWD into datasets ready for analysis
- Collaborate with cross-functional teams—including Biostatistics, Data Science, HEOR, Epidemiology/Safety, Clinical, and IT—to define data requirements and analytical strategies
- Conduct exploratory data analyses, identify patient cohorts, and perform data summary analytics to support real-world evidence (RWE) generation
- Participate in the design of RWE studies, including the development of methodologies, data analysis, interpretation, and reporting of study results
- Author or review study documents such as protocols, statistical analysis plans, study reports, publications, and study-level specifications
- Develop and maintain documentation detailing data sources, transformations, and analytical methods
- Ensure all work complies with data governance, privacy, and regulatory standards
- Stay up to date with industry and regulatory trends, tools, and best practices in RWD/RWE analytics
- Continually expand technical knowledge of statistical considerations in real-world evidence generation to ensure high-quality study design and analysis
- Enhance understanding of the drug development process, as well as regulatory and commercial requirements
Required Qualifications
- Master's or PhD in Epidemiology, Biostatistics, Data Science, Health Informatics, or a related field
- + years of experience working with real-world healthcare data (claims, EMR, registries, etc.)
- + years of experience in pharmaceutical industry (e.g. Pharma, CRO, Biotech) and clinical trials
- Proficiency in SAS, R, Python, or similar tools for data manipulation and analysis
Preferred Qualifications
- AI/ML knowledge
- Good understanding of regulatory requirements & clinical trial design
Skills Required
- Good verbal and written communication skills in English
- Good understanding of industry RWD vendor database
- Experience with RWD data curation, engineering, exploration, and quality control in large-scale datasets
- RWD trial design and analysis experience
- Ability to communicate complex real-world data concepts to non-technical stakeholders
- Ability to work successfully within cross-functional teams
- Ability to organize multiple work assignments and establish priorities
- Strong understanding of healthcare industry regulatory compliant data standards
Locations
- Warsaw, United States
Salary
Salary not disclosed
Estimated Salary Rangemedium confidence
150,000 - 220,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Good verbal and written communication skills in Englishintermediate
- Good understanding of industry RWD vendor databaseintermediate
- Experience with RWD data curation, engineering, exploration, and quality control in large-scale datasetsintermediate
- RWD trial design and analysis experienceintermediate
- Ability to communicate complex real-world data concepts to non-technical stakeholdersintermediate
- Ability to work successfully within cross-functional teamsintermediate
- Ability to organize multiple work assignments and establish prioritiesintermediate
- Strong understanding of healthcare industry regulatory compliant data standardsintermediate
Required Qualifications
- Master's or PhD in Epidemiology, Biostatistics, Data Science, Health Informatics, or a related field (experience)
- + years of experience working with real-world healthcare data (claims, EMR, registries, etc.) (experience)
- + years of experience in pharmaceutical industry (e.g. Pharma, CRO, Biotech) and clinical trials (experience)
- Proficiency in SAS, R, Python, or similar tools for data manipulation and analysis (experience)
Preferred Qualifications
- AI/ML knowledge (experience)
- Good understanding of regulatory requirements & clinical trial design (experience)
Responsibilities
- Curate and assess the quality of real-world data (RWD) assets to ensure their suitability and understanding for intended use
- Design and implement data pipelines to transform raw RWD into datasets ready for analysis
- Collaborate with cross-functional teams—including Biostatistics, Data Science, HEOR, Epidemiology/Safety, Clinical, and IT—to define data requirements and analytical strategies
- Conduct exploratory data analyses, identify patient cohorts, and perform data summary analytics to support real-world evidence (RWE) generation
- Participate in the design of RWE studies, including the development of methodologies, data analysis, interpretation, and reporting of study results
- Author or review study documents such as protocols, statistical analysis plans, study reports, publications, and study-level specifications
- Develop and maintain documentation detailing data sources, transformations, and analytical methods
- Ensure all work complies with data governance, privacy, and regulatory standards
- Stay up to date with industry and regulatory trends, tools, and best practices in RWD/RWE analytics
- Continually expand technical knowledge of statistical considerations in real-world evidence generation to ensure high-quality study design and analysis
- Enhance understanding of the drug development process, as well as regulatory and commercial requirements
Tags & Categories
Senior Manager, Real World Evidence Analyst - Starszy Manager ds. Analityki Rzeczywistych Dowodów (Real World Evidence - RWE)
Bristol-Myers Squibb
Senior Manager, Real World Evidence Analyst - Starszy Manager ds. Analityki Rzeczywistych Dowodów (Real World Evidence - RWE)
Job Description
Curate and assess the quality of real-world data (RWD) assets to ensure their suitability and understanding for intended use. Design and implement data pipelines to transform raw RWD into datasets ready for analysis. Collaborate with cross-functional teams—including Biostatistics, Data Science, HEOR, Epidemiology/Safety, Clinical, and IT—to define data requirements and analytical strategies. Conduct exploratory data analyses, identify patient cohorts, and perform data summary analytics to support real-world evidence (RWE) generation. Participate in the design of RWE studies, including the development of methodologies, data analysis, interpretation, and reporting of study results. Author or review study documents such as protocols, statistical analysis plans, study reports, publications, and study-level specifications. Develop and maintain documentation detailing data sources, transformations, and analytical methods. Ensure all work complies with data governance, privacy, and regulatory standards. Stay up to date with industry and regulatory trends, tools, and best practices in RWD/RWE analytics. Continually expand technical knowledge of statistical considerations in real-world evidence generation to ensure high-quality study design and analysis. Enhance understanding of the drug development process, as well as regulatory and commercial requirements. Supporting People with Disabilities Master's or PhD in Epidemiology, Biostatistics, Data Science, Health Informatics, or a related field. 3+ years of experience working with real-world healthcare data (claims, EMR, registries, etc.). 2+ years of experience in pharmaceutical industry (e.g. Pharma, CRO, Biotech) and clinical trials. Proficiency in SAS, R, Python, or similar tools for data manipulation and analysis. AI/ML knowledge is a plus. Good verbal and written communication skills in English Good understanding of industry RWD vendor database. Experience with RWD data curation, engineering, exploration, and quality control in large-scale datasets. RWD trial design and analysis experience Ability to communicate complex real-world data concepts to non-technical stakeholders. Ability to work successfully within cross-functional teams Ability to organize multiple work assignments and establish priorities Strong understanding of healthcare industry regulatory compliant data standards. Good understanding of regulatory requirements & clinical trial design is preferred.
Key Responsibilities
- Curate and assess the quality of real-world data (RWD) assets to ensure their suitability and understanding for intended use
- Design and implement data pipelines to transform raw RWD into datasets ready for analysis
- Collaborate with cross-functional teams—including Biostatistics, Data Science, HEOR, Epidemiology/Safety, Clinical, and IT—to define data requirements and analytical strategies
- Conduct exploratory data analyses, identify patient cohorts, and perform data summary analytics to support real-world evidence (RWE) generation
- Participate in the design of RWE studies, including the development of methodologies, data analysis, interpretation, and reporting of study results
- Author or review study documents such as protocols, statistical analysis plans, study reports, publications, and study-level specifications
- Develop and maintain documentation detailing data sources, transformations, and analytical methods
- Ensure all work complies with data governance, privacy, and regulatory standards
- Stay up to date with industry and regulatory trends, tools, and best practices in RWD/RWE analytics
- Continually expand technical knowledge of statistical considerations in real-world evidence generation to ensure high-quality study design and analysis
- Enhance understanding of the drug development process, as well as regulatory and commercial requirements
Required Qualifications
- Master's or PhD in Epidemiology, Biostatistics, Data Science, Health Informatics, or a related field
- + years of experience working with real-world healthcare data (claims, EMR, registries, etc.)
- + years of experience in pharmaceutical industry (e.g. Pharma, CRO, Biotech) and clinical trials
- Proficiency in SAS, R, Python, or similar tools for data manipulation and analysis
Preferred Qualifications
- AI/ML knowledge
- Good understanding of regulatory requirements & clinical trial design
Skills Required
- Good verbal and written communication skills in English
- Good understanding of industry RWD vendor database
- Experience with RWD data curation, engineering, exploration, and quality control in large-scale datasets
- RWD trial design and analysis experience
- Ability to communicate complex real-world data concepts to non-technical stakeholders
- Ability to work successfully within cross-functional teams
- Ability to organize multiple work assignments and establish priorities
- Strong understanding of healthcare industry regulatory compliant data standards
Locations
- Warsaw, United States
Salary
Salary not disclosed
Estimated Salary Rangemedium confidence
150,000 - 220,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Good verbal and written communication skills in Englishintermediate
- Good understanding of industry RWD vendor databaseintermediate
- Experience with RWD data curation, engineering, exploration, and quality control in large-scale datasetsintermediate
- RWD trial design and analysis experienceintermediate
- Ability to communicate complex real-world data concepts to non-technical stakeholdersintermediate
- Ability to work successfully within cross-functional teamsintermediate
- Ability to organize multiple work assignments and establish prioritiesintermediate
- Strong understanding of healthcare industry regulatory compliant data standardsintermediate
Required Qualifications
- Master's or PhD in Epidemiology, Biostatistics, Data Science, Health Informatics, or a related field (experience)
- + years of experience working with real-world healthcare data (claims, EMR, registries, etc.) (experience)
- + years of experience in pharmaceutical industry (e.g. Pharma, CRO, Biotech) and clinical trials (experience)
- Proficiency in SAS, R, Python, or similar tools for data manipulation and analysis (experience)
Preferred Qualifications
- AI/ML knowledge (experience)
- Good understanding of regulatory requirements & clinical trial design (experience)
Responsibilities
- Curate and assess the quality of real-world data (RWD) assets to ensure their suitability and understanding for intended use
- Design and implement data pipelines to transform raw RWD into datasets ready for analysis
- Collaborate with cross-functional teams—including Biostatistics, Data Science, HEOR, Epidemiology/Safety, Clinical, and IT—to define data requirements and analytical strategies
- Conduct exploratory data analyses, identify patient cohorts, and perform data summary analytics to support real-world evidence (RWE) generation
- Participate in the design of RWE studies, including the development of methodologies, data analysis, interpretation, and reporting of study results
- Author or review study documents such as protocols, statistical analysis plans, study reports, publications, and study-level specifications
- Develop and maintain documentation detailing data sources, transformations, and analytical methods
- Ensure all work complies with data governance, privacy, and regulatory standards
- Stay up to date with industry and regulatory trends, tools, and best practices in RWD/RWE analytics
- Continually expand technical knowledge of statistical considerations in real-world evidence generation to ensure high-quality study design and analysis
- Enhance understanding of the drug development process, as well as regulatory and commercial requirements
Tags & Categories