Post job

Biostatistician vs principal statistical scientist

The differences between biostatisticians 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 biostatistician and a principal statistical scientist. Additionally, a principal statistical scientist has an average salary of $108,113, which is higher than the $85,645 average annual salary of a biostatistician.

The top three skills for a biostatistician include data analysis, patients and data management. The most important skills for a principal statistical scientist are clinical trials, data analysis, and experimental design.

Biostatistician vs principal statistical scientist overview

BiostatisticianPrincipal Statistical Scientist
Yearly salary$85,645$108,113
Hourly rate$41.18$51.98
Growth rate31%31%
Number of jobs17,97278,916
Job satisfaction--
Most common degreeBachelor's Degree, 47%Bachelor's Degree, 54%
Average age3737
Years of experience22

Biostatistician vs principal statistical scientist salary

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

BiostatisticianPrincipal Statistical Scientist
Average salary$85,645$108,113
Salary rangeBetween $60,000 And $120,000Between $71,000 And $163,000
Highest paying CitySan Francisco, CASan Francisco, CA
Highest paying stateCaliforniaNevada
Best paying companyMetaGenentech
Best paying industryPharmaceutical-

Differences between biostatistician and principal statistical scientist education

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

BiostatisticianPrincipal Statistical Scientist
Most common degreeBachelor's Degree, 47%Bachelor's Degree, 54%
Most common majorStatisticsStatistics
Most common collegeJohns Hopkins UniversityNorthwestern University

Biostatistician vs principal statistical scientist demographics

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

BiostatisticianPrincipal Statistical Scientist
Average age3737
Gender ratioMale, 55.8% Female, 44.2%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 biostatistician and principal statistical scientist duties and responsibilities

Biostatistician example responsibilities.

  • Extract and manage data from different sources, proficient in query language SQL.
  • Act as project director for managing the preparation of safety and efficacy reports for NDA submission.
  • Manage Medicaid fraud and abuse portfolios by analyzing medical and pharmacy claims data.
  • Provide suggestions to clients in classification algorithms, ANOVA, experimental design, and various hypothesis tests.
  • Design clinical plans, new product or improvement protocols, co-ordinate CRO and clinical site contracts and IRB submissions.
  • Create views using SQL programming.
  • 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.

Biostatistician vs principal statistical scientist skills

Common biostatistician skills
  • Data Analysis, 9%
  • Patients, 7%
  • Data Management, 6%
  • Statistical Analysis, 5%
  • Study Design, 5%
  • Data Collection, 4%
Common principal statistical scientist skills
  • Clinical Trials, 47%
  • Data Analysis, 42%
  • Experimental Design, 7%
  • Statistical Analyses, 4%
  • Internal Training, 0%

Browse computer and mathematical jobs