Ex-US Operations-Real World Analyst III

5 months ago

Hyderabad, Telangana, India Bristol Myers Squibb Full time

BMS Hyderabad is an integrated global hub where our work is focused on helping patients prevail over serious diseases by building sustainable and innovative solutions. This important science, technology, and innovation center will support a range of technology and drug development activities that will help us usher in the next wave of innovation.

#GBOHYD #LI-Hybrid

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.

#GBOHYD #LI-Hybrid

This role mandatorily needs to have working knowledge of SQL, having European Market exposure and min 5 years of total work experience.

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.

Oversee and 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

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

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

Provide training, guidance and mentorship to junior analysts and team members as required

Experience

Bachelor's or Master's degree in a relevant field, such as Biostatistics, Epidemiology, Health Informatics, or a related discipline.

Proven experience (typically 5+ years) 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.

Experience with R or SAS and data visualization tools, such as Tableau or Power BI, is desirable.

Candidates should have SQL experience

Familiarity with relevant statistical methodologies and study designs used in real-world data analysis.

Understanding of regulatory requirements and guidelines related to real-world data use, such as FDA's Real-World Evidence Program or similar initiatives.

Candidates should have experience in BioPharma, Healthcare or Life Science industry.

Skills & Competencies

Strong understanding of real-world data sources, such as electronic health records (EHR), 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

Excellent problem-solving skills and the ability to derive meaningful insights from complex real-world data sets

Excellent 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

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