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Biostatistics director vs principal statistical scientist

The differences between biostatistics directors and principal statistical scientists can be seen in a few details. Each job has different responsibilities and duties. It typically takes 1-2 years to become both a biostatistics director and a principal statistical scientist. Additionally, a principal statistical scientist has an average salary of $108,113, which is higher than the $58,329 average annual salary of a biostatistics director.

The top three skills for a biostatistics director include SAS, CRO and regulatory submissions. The most important skills for a principal statistical scientist are clinical trials, data analysis, and experimental design.

Biostatistics director vs principal statistical scientist overview

Biostatistics DirectorPrincipal Statistical Scientist
Yearly salary$58,329$108,113
Hourly rate$28.04$51.98
Growth rate31%31%
Number of jobs6,11578,916
Job satisfaction--
Most common degreeBachelor's Degree, 44%Bachelor's Degree, 54%
Average age3737
Years of experience22

Biostatistics director vs principal statistical scientist salary

Biostatistics directors and principal statistical scientists have different pay scales, as shown below.

Biostatistics DirectorPrincipal Statistical Scientist
Average salary$58,329$108,113
Salary rangeBetween $26,000 And $130,000Between $71,000 And $163,000
Highest paying City-San Francisco, CA
Highest paying state-Nevada
Best paying company-Genentech
Best paying industry--

Differences between biostatistics director and principal statistical scientist education

There are a few differences between a biostatistics director and a principal statistical scientist in terms of educational background:

Biostatistics DirectorPrincipal Statistical Scientist
Most common degreeBachelor's Degree, 44%Bachelor's Degree, 54%
Most common majorStatisticsStatistics
Most common collegeUniversity of PennsylvaniaNorthwestern University

Biostatistics director vs principal statistical scientist demographics

Here are the differences between biostatistics directors' and principal statistical scientists' demographics:

Biostatistics DirectorPrincipal Statistical Scientist
Average age3737
Gender ratioMale, 79.2% Female, 20.8%Male, 76.9% Female, 23.1%
Race ratioBlack or African American, 5.1% Unknown, 5.0% Hispanic or Latino, 7.6% Asian, 22.7% White, 59.4% American Indian and Alaska Native, 0.2%Black or African American, 5.1% Unknown, 5.0% Hispanic or Latino, 7.6% Asian, 22.7% White, 59.4% American Indian and Alaska Native, 0.2%
LGBT Percentage9%9%

Differences between biostatistics director and principal statistical scientist duties and responsibilities

Biostatistics director example responsibilities.

  • Act as project director for managing the preparation of safety and efficacy reports for NDA submission.
  • Support electronic regulatory submission which include STDM, CDISC standards.
  • Create and maintain standard QC notebooks for clinical research studies.
  • Conduct validation and QC on the deliverables from internal staff.
  • Act as the internal CDSIC expert on SDTM and ADaM principles and implementation.
  • Develop SAS programs for statistical analyses and generating data tables, figures and listings.
  • Show more

Principal statistical scientist example responsibilities.

  • Manage pediatric dose development project, technology transfer project and alternate API supplier qualification project on budget and on schedule
  • Conduct research and analyze data to identify potential biomarkers and provide input for selection of candidates for non-clinical studies development.
  • Facilitate customer acceptance of demand forecast by developing visualization processes, tutoring clients in methodology, and providing detail walk-through examples.

Biostatistics director vs principal statistical scientist skills

Common biostatistics director skills
  • SAS, 18%
  • CRO, 10%
  • Regulatory Submissions, 9%
  • Study Design, 8%
  • Biometrics, 8%
  • Statistical Analysis, 8%
Common principal statistical scientist skills
  • Clinical Trials, 47%
  • Data Analysis, 42%
  • Experimental Design, 7%
  • Statistical Analyses, 4%
  • Internal Training, 0%

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