Biostatistician / Statistical Data Analyst
Title: Biostatistician / Statistical Data Analyst
Location: Contractor Site (Remote or On-site as needed)
Clearance Level: Not required
Period of Performance: August 1, 2025 - July 31, 2030
Contract Reference: RFQ No. 75F40125Q00292
Hourly Pay Rate: $60.50/hour
Role Summary:
Provides statistical modeling, longitudinal analysis, and hypothesis testing for omics-based FDA clinical trial studies. Supports biomarker discovery by modeling drug response over time using validated methods.
Key Responsibilities:
• Perform descriptive statistics and transformation on omics datasets
• Apply GEE and mixed-effects models for repeated measures analysis
• Use BH and Bonferroni methods for multiple testing corrections
• Analyze drug*time interaction and peak response timepoints
• Calculate AUEC and rank candidate biomarkers by significance and effect size
• Adjust for confounders (age, gender, BMI) in statistical models
Education:
• Required: Master's in Biostatistics, Epidemiology, or Statistics
• Preferred: Ph.D. in Biostatistics or Quantitative Health Science
Experience:
• 5+ years in clinical or translational omics research
• Strong knowledge of longitudinal modeling, statistical significance testing
• Familiarity with baseline adjustment and RFU datasets
Tools & Skills:
• R (lme4, nlme), SAS, Python (statsmodels)
• Experience with repeated measures, biomarker timecourse analyses
Certifications (Preferred):
• Certified Biostatistician (CB)
• SAS Advanced Programmer Certification
Apply Now
Apply Now
Location: Contractor Site (Remote or On-site as needed)
Clearance Level: Not required
Period of Performance: August 1, 2025 - July 31, 2030
Contract Reference: RFQ No. 75F40125Q00292
Hourly Pay Rate: $60.50/hour
Role Summary:
Provides statistical modeling, longitudinal analysis, and hypothesis testing for omics-based FDA clinical trial studies. Supports biomarker discovery by modeling drug response over time using validated methods.
Key Responsibilities:
• Perform descriptive statistics and transformation on omics datasets
• Apply GEE and mixed-effects models for repeated measures analysis
• Use BH and Bonferroni methods for multiple testing corrections
• Analyze drug*time interaction and peak response timepoints
• Calculate AUEC and rank candidate biomarkers by significance and effect size
• Adjust for confounders (age, gender, BMI) in statistical models
Education:
• Required: Master's in Biostatistics, Epidemiology, or Statistics
• Preferred: Ph.D. in Biostatistics or Quantitative Health Science
Experience:
• 5+ years in clinical or translational omics research
• Strong knowledge of longitudinal modeling, statistical significance testing
• Familiarity with baseline adjustment and RFU datasets
Tools & Skills:
• R (lme4, nlme), SAS, Python (statsmodels)
• Experience with repeated measures, biomarker timecourse analyses
Certifications (Preferred):
• Certified Biostatistician (CB)
• SAS Advanced Programmer Certification
Apply Now
Apply Now