Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.
Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.
Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.
Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.
Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.
Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.
Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.
Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.
Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.
Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.
Professional Summary
Principal Statistical Programmer with 12 years of experience designing and implementing scalable statistical models and analysis pipelines. Specialises in R and Python solutions that inform critical clinical decisions while maintaining regulatory compliance. Proven track record of improving analysis cycle times and mentoring cross-functional teams.
Skills
- Communication
- Project Management
- Leadership
- R
- Problem Solving
- Python
- Java
- Linux
- GIT
- SAS
- Clinical Data Standards
- CDISC
Experience
Principal Statistical Programmer — Trigent Software Inc
- Architected an R-based analytics platform that reduced statistical analysis cycle time by 47% across 12 clinical programmes.
- Implemented CI/CD pipelines for SAS and R scripts, improving validation turnaround from 10 days to 2 days and increasing release cadence.
- Mentored a team of 6 programmers on CDISC compliance, resulting in 100% first-pass acceptance on regulatory submissions.
- Designed interactive dashboards using Shiny to visualise key trial endpoints, accelerating decision-making for project leadership.
- Spearheaded migration of legacy SAS workflows to R, eliminating 75% of manual error and enabling reusable analysis artefacts.
Statistical Programmer — Cytel
- Delivered analysis datasets and TFLs for 15+ late-stage oncology trials while ensuring compliance with CDISC ADaM standards.
- Automated ADaM derivation logic in R, cutting development time by 30% and improving traceability for regulatory submissions.
- Collaborated with biostatisticians to validate Bayesian adaptive designs, providing clear documentation for health authority reviews.
- Facilitated workshops on R programming best practices, lifting overall team competency and adoption of version control.
- Optimised data cleaning pipelines using dplyr and tidyverse principles, reducing defect rates in baseline datasets.