Statistical Data Scientist
Praxis Precision Medicines, Inc.
2 hours ago
Remote friendly (United States)
United States
Clinical Research and Development
Primary Responsibilities
- Lead design, development, and validation of R/Python code to automate generation of analytical datasets and TLFs within a metadata-driven pipeline.
- Translate SAPs and metadata specifications (YAML/CSV) into executable, reproducible code.
- Build and validate R packages and data science tools for exploratory and confirmatory analyses with full traceability and audit readiness.
- Implement and validate statistical models (e.g., MMRM, ANCOVA, logistic regression) using R packages such as mmrm and emmeans.
- Collaborate with IT to integrate workflows within Databricks and CI/CD pipelines for continuous validation and reproducibility.
- Collaborate across programming, biostatistics, and data standards to ensure dataset definitions, derivations, and metadata align with controlled standards.
- Conduct peer code reviews, unit testing, and automated validation to meet submission-quality and reproducibility standards.
- Mentor and guide team members in programming, validation, and automation best practices.
Qualifications
- Bachelor’s or Master’s degree in Statistics, Biostatistics, Data Science, or related field.
- 8+ years of statistical programming experience in pharmaceutical/biotech; hands-on R and/or Python.
- Proven experience supporting R-based regulatory submissions (e.g., R package validation, R-based analysis delivery, or submission readiness).
- Strong understanding of CDISC ADaM and SDTM data structures.
- Experience developing and validating reusable R/Python libraries/functions.
- Proficiency with Git, Bitbucket, and CI/CD automation pipelines.
- Working knowledge of GxP and Part 11 compliance.
- Excellent documentation and validation practices.
- Collaborative, proactive mindset; able to operate independently in a small agile team.
Preferred Experience
- YAML/JSON configuration; metadata-driven programming workflows.
- Migrating from SAS to R/Python.
- R validation frameworks (e.g., risk-based testing, reproducibility documentation).
- Exploratory analytics or visualization in R/Python within a regulated framework.
Compensation & Benefits
- Annualized Base Salary: $180,000 USD - $200,000 USD
Note: This position may be performed remotely, with flexibility to travel as needed.
- Lead design, development, and validation of R/Python code to automate generation of analytical datasets and TLFs within a metadata-driven pipeline.
- Translate SAPs and metadata specifications (YAML/CSV) into executable, reproducible code.
- Build and validate R packages and data science tools for exploratory and confirmatory analyses with full traceability and audit readiness.
- Implement and validate statistical models (e.g., MMRM, ANCOVA, logistic regression) using R packages such as mmrm and emmeans.
- Collaborate with IT to integrate workflows within Databricks and CI/CD pipelines for continuous validation and reproducibility.
- Collaborate across programming, biostatistics, and data standards to ensure dataset definitions, derivations, and metadata align with controlled standards.
- Conduct peer code reviews, unit testing, and automated validation to meet submission-quality and reproducibility standards.
- Mentor and guide team members in programming, validation, and automation best practices.
Qualifications
- Bachelor’s or Master’s degree in Statistics, Biostatistics, Data Science, or related field.
- 8+ years of statistical programming experience in pharmaceutical/biotech; hands-on R and/or Python.
- Proven experience supporting R-based regulatory submissions (e.g., R package validation, R-based analysis delivery, or submission readiness).
- Strong understanding of CDISC ADaM and SDTM data structures.
- Experience developing and validating reusable R/Python libraries/functions.
- Proficiency with Git, Bitbucket, and CI/CD automation pipelines.
- Working knowledge of GxP and Part 11 compliance.
- Excellent documentation and validation practices.
- Collaborative, proactive mindset; able to operate independently in a small agile team.
Preferred Experience
- YAML/JSON configuration; metadata-driven programming workflows.
- Migrating from SAS to R/Python.
- R validation frameworks (e.g., risk-based testing, reproducibility documentation).
- Exploratory analytics or visualization in R/Python within a regulated framework.
Compensation & Benefits
- Annualized Base Salary: $180,000 USD - $200,000 USD
Note: This position may be performed remotely, with flexibility to travel as needed.