RWE Data Analyst

Medasource; United States; On-site; USD 80,000 - 110,000; Full time

Job summary

A leading healthcare analytics firm is seeking a RWD Analyst to perform statistical analyses and QC for data visualization in Real World Evidence research. The ideal candidate will have extensive experience in Biostatistics and Epidemiology, especially in Virology HIV studies. Candidates should possess strong communication skills and be proficient in statistical analysis programs like SAS and R. This contract position requires meticulous attention to detail in data management and analysis.

Qualifications

• 3+ years in Biostatistics or Epidemiology preferred.
• 8+ years relevant experience with a Master’s degree.
• Preferred experience in Virology HIV studies.

Responsibilities

• Develop and QC TFLs for RWE research.
• Conduct thorough reviews of TFLs.
• Collaborate with the team for timely completion.

Skills

Biostatistics

Epidemiology

Statistical analysis (SAS, R)

Quality control

Data management

Statistical methodology communication

Education

Doctoral degree in Biostatistics, Epidemiology

Master’s degree in related discipline

Tools

SAS

R

Job description

Direct message the job poster from Medasource

As a member of the CDS-RWE Analytics group, the RWD Analyst reports directly Head of RWE Analytics and is responsible for the conduct of statistical analyses of RWD to assess the value of Gilead therapies and perform data visualization and QCs TFLs to communicate results to internal stakeholders in Real World Evidence. The RWD Analyst will align with the Real-World Evidence Therapeutic Area (TA)-aligned Lead to conduct timely, relevant, and rigorous analysis of RWD to address critical research questions, as well as collaborate with CDS to develop, refine, and scale data management and analytic procedures, systems, workflows, best practices, and other issues.

We are seeking a highly skilled and detail-oriented individual to join our team as a TFL Reviewer and Quality Control Specialist. The primary responsibility of this role is to meticulously review each round of Tables, Figures, and Listings (TFLs) produced in-house, with a particular focus on new TFLs created for specific requests. In cases where there is a large set of TFLs, the review will be prioritized based on importance.

Key Responsibilities

• Develop and QC TFLs for protocols/reports/manuscripts from RWE research conducted to assess the value of the client\'s therapies using RWD.
• Conduct thorough reviews of each round of TFLs, ensuring accuracy and consistency.
• Prioritize the review of new TFLs created for specific requests.
• Be available to join projects at short notice as soon as they are ready for review.
• Collaborate with the team to ensure timely and accurate completion of reviews.
• QC programming for descriptive and complex studies using RWD.
• Conduct analyses and develop specifications for descriptive and complex statistics in studies using RWD.
• Understand methods and programming to support Comparative Effectiveness Research (CER) analyses, as well as analyses of patient-reported outcomes (PRO) or other patient outcome data

Knowledge, Skills and Experience

• Doctoral level training with a minimum of three (3) years of relevant experience in Biostatistics, Epidemiology is preferred.
• Master’s degree (e.g. MA, MSc, MPH) in Biostatistics, Epidemiology or related discipline, such as Outcomes Research from an accredited institution, with a minimum of eight (8) years of relevant, post-graduation experience.
• Knowledge of real-world data and experience in observational research study design, execution and communication.
• Preferred experience in Virology HIV studies
• Experience with quality control in primary data collection studies
• Preferred have Knowledge of ADaM data structure, including documentation and best practices
• Strong track record of analysis of a broad range of RWD.
• Strong understanding of significance testing and sample size checking.
• Knowledge of data distributions and the logic of footnotes.
• Ability to understand how data interrelate and hang together.
• Formal training in Programming and demonstrated proficiency in statistical analysis programs commonly used in life sciences (e.g. SAS, R).
• Capability to double-program studies or certain tables as necessary.
• Understanding of epidemiology or outcomes research and the application of retrospective or prospective studies to generate value evidence.
• Ability to effectively communicate statistical methodology and analysis results.
• Ability to work effectively in a constantly changing, diverse, and matrix environment.
• Knowledge of US secondary data sources and experience with international data sources is optional
• Knowledge and experience in qualitative analysis and data sets (e.g., free-text natural language processing, survey data) is preferred.

Data sources

Databases used listed below:

Databases mentioned include primary data and ADaM data structure

Seniority level

• Mid-Senior level

Employment type

• Contract

Job function

• Analyst

Industries

• Pharmaceutical Manufacturing
• Biotechnology Research
• Hospitals and Health Care