Biostatistician II

About the role

At Thermo Fisher Scientific, you’ll discover meaningful work that makes a positive impact on a global scale. As part of our clinical research portfolio, our CorEvitas evidence-based solutions specialize in generating data intelligence and clinical insights needed to bring safe and effective treatments to market. The Biostatistics team for the Real-World Science department uses specialized statistical expertise to perform analyses such as assessing prescribing patterns, comparing effectiveness between treatments, and investigating differences in safety outcomes using complex longitudinal prospective and registry data.

The Biostatistician II will work under the guidance of a Biostatistical Team Lead to implement statistical analysis plans involving complex longitudinal registry data available in several autoimmune disease areas. This individual will help to prepare appropriate analytic summaries and context for reports and publications.

Responsibilities

• Compiles, analyzes, and reports statistical data for various projects
• Conducts complex statistical analyses with supervision in accordance with statistical analysis plans
• Supports the Biostatistical Team Lead in developing new statistical methodologies for data analysis
• Applies advanced statistical methods, which may include simulation models and other statistical programming, as needed
• Reviews relevant literature and existing data, assesses data quality, and demonstrates increasing independence in statistical decision-making
• Contributes to research projects and takes initiative in professional activities
• Closely collaborates and participates in knowledge sharing with other statistical analysts
• Utilizes various database management systems as required

Requirements

• Master's degree in Biostatistics, Statistics, Bioinformatics, Mathematics, or a related field required
• 2 years at a minimum of applied statistical experience required
• Experience working with complex longitudinal datasets and applying advanced statistical methods is required
• Experience with coding with SAS and R is required
• Experience with GitHub is preferred

Skills

• Proficiency in both R and SAS for data manipulation and statistical analyses
• Highly organized and detail-oriented, with excellent time management skills and the ability to prioritize tasks
• Strong communication skills and the ability to work independently and as part of a team
• Clear writing skills and must follow best practices for commenting of programming code

Schedule

Standard (Mon-Fri)