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Senior Statistical Data Scientist

Pfizer

Makati, National Capital Region, PhilippinesOn Site

Original Job Summary

Job Summary:

The Senior Statistical Data Scientist role at Pfizer involves hands-on programming to deliver high quality statistical programming deliverables supporting clinical study teams. The candidate will work independently and collaboratively to deliver analysis ready datasets, tables, listings, and figures, ensuring adherence to quality standards.

Role Responsibilities:

  • Deliver quality and timely datasets and displays for clinical study reports.
  • Ensure proper documentation and QC across study lifecycle.
  • Collaborate with statisticians and programming leads for clear specifications.
  • Apply knowledge of core safety, therapeutic area, and regulatory standards.
  • Contribute to department-level initiatives when needed.

Experience & Skills:

  • Bachelor or Master Degree in Statistics, Biological Sciences, IT, or related field.
  • Minimum 3 years of relevant experience in pharmaceutical, biotech, CRO, or regulatory agencies.
  • Strong written, oral communication and project management skills.
  • Proficient in Statistical Programming using SAS, R, or Python.

Preferrable but Optional:

  • Clinical trials expertise and understanding of clinical data operations.
  • Knowledge of ICH, regulatory guidelines and CDISC standards.
  • Experience with at least one Therapeutic Area.

Additional Information:

This is a Hybrid work arrangement with a flexible work location assignment. Pfizer is an equal opportunity employer that complies with local EEO legislation.

Key skills/competency:

  • Statistical Programming
  • Data Analysis
  • SAS
  • Python
  • R
  • Clinical Trials
  • Quality Control
  • Documentation
  • Regulatory Standards
  • Problem Solving

How to Get Hired at Pfizer

🎯 Tips for Getting Hired

  • Customize your resume: Highlight statistical programming and clinical experience.
  • Research Pfizer: Understand their mission and recent drug developments.
  • Demonstrate proficiency: Emphasize SAS, R, and Python skills.
  • Prepare examples: Share projects that meet strict quality standards.

📝 Interview Preparation Advice

Technical Preparation

Review SAS programming practices and guidelines.
Practice building analysis ready datasets.
Update Python and R coding skills.
Study regulatory data standards thoroughly.

Behavioral Questions

Describe managing tight deadlines effectively.
Explain collaboration with cross-functional teams.
Discuss problem-solving in challenging data scenarios.
Share experiences with quality assurance processes.