Lead RWE Biostatistician & Analytics Architect

Stryker Group; Hinoba-an; On-site; PHP 550,000 - 1,200,000; Full time

Job summary

Stryker Group in the Philippines seeks an experienced statistician/statistical programmer to lead in-house analyses for real-world evidence studies within Clinical Affairs. The role emphasizes SAP development, SAS programming, and reproducible methods.

You will collaborate across divisions, automate analyses, and mentor junior staff while leveraging R, Python, SQL, Power BI and Tableau. HIPAA/GDPR knowledge and large healthcare databases are preferred.

Qualifications

• 5–8 years as statistician or statistical programmer with at least 2+ years of real-world data (RWD) experience.
• Strong understanding of statistical methods used in real-world evidence (RWE) studies.
• Experience leading analyses to meet regulatory requirements within budgets and timelines.

Responsibilities

• Contribute to RWE study design and SAP development.
• Perform SAS programming and analyses; validate programs for tables, listings, figures, and datasets.
• Develop macros to automate standard analyses and improve efficiency.
• Document projects for reproducibility; oversee external contractors.
• Train and mentor junior staff; share knowledge with internal partners.
• Identify improvements in RWE workflows and data quality.
• Ensure SOPs and documentation are maintained.

Skills

SAS programming

R

Python

SQL

STATA

Power BI

Tableau

Databricks

Cloud computing

HIPAA/GDPR knowledge

Tools

Premier Healthcare Database

Truven MarketScan

OMOP/CDM

Job description

Stryker Group in the Philippines seeks an experienced statistician/statistical programmer to lead in-house analyses for real-world evidence studies within Clinical Affairs. The role emphasizes SAP development, SAS programming, and reproducible methods.

You will collaborate across divisions, automate analyses, and mentor junior staff while leveraging R, Python, SQL, Power BI and Tableau. HIPAA/GDPR knowledge and large healthcare databases are preferred.