Real World Data Analyst I

6 days ago

Hyderabad, Telangana, India Bristol Myers Squibb Full time

About Bristol Myers Squibb: At Bristol Myers Squibb, we are inspired by a single vision transforming patients lives through science. In oncology, hematology, immunology, and cardiovascular disease and one of the most diverse and promising pipelines in the industry each of our passionate colleagues contribute to innovations that drive meaningful change. We bring a human touch to every treatment we pioneer. Join us and make a difference. Summary: The Real-World Data (RWD) Analyst will play a critical role within BIA Hyderabad. This specialized position focuses on analyzing and deriving insights from real-world data sources to generate evidence and support decision-making across the organization. The RWD Analyst will leverage a variety of RWD and evidence analytics techniques to contribute to research, clinical development, market access, and post-marketing activities. Roles & Responsibilities: Collaborate with cross-functional teams, including researchers, clinicians, market access and regulatory stakeholders, to understand data needs and objectives for RWD analysis Identify relevant real-world data from various sources, such as electronic health records (EHRs), claims databases, registries and other healthcare databases Clean, transform and preprocess real-world data to ensure data quality, consistency and compatibility for analysis Apply appropriate statistical techniques to analyze real-world data and generate insights on research questions or business objectives Partner with senior analysts to conduct observational studies, comparative effectiveness research (CER), patient outcomes research and other types of RWD analysis to evaluate treatment outcomes, safety profiles and healthcare utilization patterns Partner with senior analysts to develop and implement data analysis plans, including study designs, statistical methodologies and modelling approaches Interpret and communicate findings from RWD analysis through reports, presentations and visualizations to stakeholders Partner with senior analysts to collaborate with internal and external teams to design RWD studies, including protocol development, data collection and analysis Stay updated and compliant with the regulatory landscape related to real-world data analysis Contribute to the development and implementation of RWD strategies and best practices within the organization Skills and competencies: Strong understanding of real-world data sources, such as electronic health records, claims databases, registries and other healthcare databases Proficiency in data pre-processing, cleaning and transformation techniques to ensure data quality and compatibility for analysis Knowledge of relevant statistical methodologies, including propensity score matching, survival analysis and regression models, for real-world data analysis Solid problem-solving skills and the ability to derive meaningful insights from complex real-world data sets Solid communication and presentation skills to effectively convey complex concepts and findings Ability to work collaboratively in cross-functional teams and manage multiple projects simultaneously Strong attention to detail and accuracy in data analysis and interpretation Experience: A Bachelor's or Master's degree (preferred) in a relevant field, such as Biostatistics, Epidemiology, Health Informatics or a related discipline Minimum 2-3 years experience demonstrated in real-world data analysis, preferably within the biopharma or healthcare industry Experience applying statistical and analytical techniques, such as observational study design, CER, patient outcomes research, and data modelling, to analyze real-world data Proficiency in R or SAS and SQL required Working knowledge of data visualization tools, such as Tableau or Power BI, is desirable Working knowledge and familiarity with relevant statistical methodologies and study designs used in real-world data analysis Experience or familiarity with the biopharma industry or healthcare domains is preferred

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