Biostatistician II

Thermo Fisher Scientific

Biostatistician II performing statistical analysis and developing methodologies for healthcare research projects at Thermo Fisher Scientific. Collaborating with teams and conducting advanced statistical analyses.

Posted 4/23/2026full-timeRemote • North Carolina • 🇺🇸 United StatesMid-LevelSeniorWebsite

About the role

Key responsibilities & impact

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

What you’ll need

Master's degree in Biostatistics, Statistics, Bioinformatics, Mathematics or related field is required.
A minimum of 3 years of applied statistical experience is required.
Experience programming in R for data manipulation and statistical analysis is required.
Experience programming in SAS is preferred.
Experience equivalent to 3 years working with complex longitudinal datasets and applying advanced statistical methods is preferred.
Experience with causal inference theory and methods is a plus.
Must be highly organized and detail-oriented, with excellent time management skills and the ability to prioritize tasks.
Must possess strong communication skills and be able to work independently and as part of a team.
Requires clear writing skills and must follow best practices for commenting of programming code.

Benefits

Comp & perks

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Hard Skills & Tools

statistical analysisadvanced statistical methodssimulation modelsdata manipulationprogramming in Rprogramming in SAScausal inference theorylongitudinal datasetsdata quality assessmentstatistical decision-making

Soft Skills

highly organizeddetail-orientedtime managementprioritizationstrong communicationindependent workteam collaborationinitiativeknowledge sharingclear writing