Senior RWD Programmer/Analyst - California, United States - Simulstat

Description

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Remote, 12-month contract with potential to extend

As a member of the core RWE Analytics group, individuals will have access to real-world databases and act as the stewards of best practices, standards, and methodologies underlying the use of real-world data (RWD). The incumbent will design and conduct statistical analyses of RWD to assess the value of therapies and perform data visualization and QCs TFLs to communicate results to internal stakeholders. The RWD Programmer will conduct timely, relevant and rigorous analysis of RWD to address critical research questions, as well as collaborate with epidemiologists and other scientists to develop, refine, and scale data management and analytics procedures, systems, workflows, best practices, and other issues.

Key Responsibilities:

• Conduct analyses and develop specifications for descriptive and complex statistics in studies using RWD for HEOR research questions.
• Conduct analyses to inform parameters for economic models.
• Conduct effectiveness analyses of patient reported outcomes.
• In collaboration with HEOR leads select appropriate internal database to address research questions.
• Develop and QC TFLs for protocols/reports/manuscripts from RWE research conducted to assess the value of therapies using RWD (e.g. claims and EHR).
• QC programming for descriptive and complex studies in RWD.
• Work with epidemiologists and HEOR scientists to generate code lists for new measures in RWD.

Knowledge, Skills and Experience:

• Master's degree (e.g. MA, MSc, MPH) in Biostatistics, Epidemiology, Health Services Researcher, Pharmaceutical Economics and Policy, or related discipline, such as Outcomes Research from an accredited institution, with a minimum of six (6) years of relevant, post-graduation experience.
• Doctoral level training with a minimum of two (2) years of relevant experience is preferred. Direct experience in lieu of academic training is acceptable.
• Strong track record of analysis of real-world data (RWD).
• Understanding of the analysis of data to inform economic models
• Understanding of the quantitative validation of patient reported outcomes
• Formal training in Programming and demonstrated proficiency in statistical analysis using SAS. R, SQL, and Python a plus.
• Understanding of epidemiology, outcomes research, policy research, and the application of retrospective or prospective studies to generate value evidence.
• Knowledge of US secondary data sources required; additional experience with international data sources is preferred.
• Experience in observational research study design, execution and communication a plus.
• Writing Statistical Analysis Plans (SAP) for descriptive and complex studies in RWD, including claims and EHR a plus.

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