Clinical PK Data Analyst - Programming
Planet Pharma, Redwood City, CA, United States
The Opportunity:
Clinical PK Data Analyst
We are seeking a highly skilled clinical PK Data Analyst with proficiency in R and SQL programming to join the Clinical Pharmacology team within the Nonclinical Development and Clinical Pharmacology (NDCP) organization. The ideal candidate will leverage expertise in R and SQL programming to mine the databases for drug-drug interaction (DDI) and exploratory analyses. This role involves working with diverse clinical datasets and relational databases.
Duties & Responsibilities
Programming & Scripting in R:
Write clean, efficient, and reproducible R code for statistical analyses.
Develop and maintain R scripts for data manipulation, statistical testing, and data visualization.
Develop R Shiny applications or R packages to support data mining from databases; familiarity with SQL or APIs is required.
Ensure all code is well documented for future use by the team.
Data Wrangling & Preprocessing:
Collect, clean, and preprocess data from various sources to prepare it for analysis.
Handle missing data, perform data transformations, and ensure data integrity.
Visualization & Reporting:
Create clear and informative data visualizations (e.g., using ggplot2, Shiny) to communicate complex results to non-technical stakeholders.
Documentation & Version Control:
Maintain comprehensive documentation for all code, models, and processes.
Use version control tools (e.g., Git) to manage code changes and collaborate with team members.
Required Skills, Experience And Education
Master’s degree or higher in Statistics, Mathematics, Computer Science, Data Science, or a related field.
At least 2-3 years of experience in statistical programming, data analysis, or a related field.
Familiarity with SDTM/ADaM datasets.
Proven experience with R and associated libraries (e.g., dplyr, tidyr, ggplot2, table1, etc.).
Proficiency in data manipulation, cleaning, and transformation techniques using R.
Familiarity with version control (Git, GitHub, GitLab).
Experience with data visualization tools (e.g., ggplot2, Shiny).
Working knowledge of SQL or APIs.
Preferred Skills
Ability to troubleshoot and optimize complex R code.
Familiarity with large language models (LLM) is a plus.
Strong written and verbal communication skills.
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Clinical PK Data Analyst
We are seeking a highly skilled clinical PK Data Analyst with proficiency in R and SQL programming to join the Clinical Pharmacology team within the Nonclinical Development and Clinical Pharmacology (NDCP) organization. The ideal candidate will leverage expertise in R and SQL programming to mine the databases for drug-drug interaction (DDI) and exploratory analyses. This role involves working with diverse clinical datasets and relational databases.
Duties & Responsibilities
Programming & Scripting in R:
Write clean, efficient, and reproducible R code for statistical analyses.
Develop and maintain R scripts for data manipulation, statistical testing, and data visualization.
Develop R Shiny applications or R packages to support data mining from databases; familiarity with SQL or APIs is required.
Ensure all code is well documented for future use by the team.
Data Wrangling & Preprocessing:
Collect, clean, and preprocess data from various sources to prepare it for analysis.
Handle missing data, perform data transformations, and ensure data integrity.
Visualization & Reporting:
Create clear and informative data visualizations (e.g., using ggplot2, Shiny) to communicate complex results to non-technical stakeholders.
Documentation & Version Control:
Maintain comprehensive documentation for all code, models, and processes.
Use version control tools (e.g., Git) to manage code changes and collaborate with team members.
Required Skills, Experience And Education
Master’s degree or higher in Statistics, Mathematics, Computer Science, Data Science, or a related field.
At least 2-3 years of experience in statistical programming, data analysis, or a related field.
Familiarity with SDTM/ADaM datasets.
Proven experience with R and associated libraries (e.g., dplyr, tidyr, ggplot2, table1, etc.).
Proficiency in data manipulation, cleaning, and transformation techniques using R.
Familiarity with version control (Git, GitHub, GitLab).
Experience with data visualization tools (e.g., ggplot2, Shiny).
Working knowledge of SQL or APIs.
Preferred Skills
Ability to troubleshoot and optimize complex R code.
Familiarity with large language models (LLM) is a plus.
Strong written and verbal communication skills.
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