Data Scientist

Data Scientist Overview

• The Data Scientist role combines programming, biostatistics, and clinical data management expertise to develop innovative solutions for clinical analytics.
• Collaborate with cross-functional teams to create tools for efficient data access, analysis, and visualization.
• Support ongoing clinical studies while building reusable technical infrastructure for the Biometrics organization.
• Utilize R, SAS, and Python to address complex analytical challenges and develop interactive applications.
• Promote modern programming practices, automation, and collaborative development workflows within the organization.
• Contribute to the growth of the organization's clinical analytics capabilities through innovation and technical expertise.
• Work remotely as a contractor, providing flexibility and autonomy in project execution.

Data Scientist Key Responsibilities & Duties

• Develop data science solutions and analytical tools for clinical studies and Biometrics initiatives.
• Design and implement dashboards and visualizations for effective clinical data review and decision-making.
• Create reusable tools and workflows to enhance team efficiency in data management and analysis.
• Build and maintain automated workflows using GitHub and GitHub Actions for quality assurance.
• Develop interactive analytical applications using R Shiny to support clinical analytics.
• Collaborate with Biostatistics, Statistical Programming, and Data Management teams to understand study needs.
• Identify opportunities for automation and introduce innovative solutions to improve processes.
• Mentor team members in adopting modern programming and application development practices.

Data Scientist Job Requirements

• Bachelor's or Master's degree in Data Science, Statistics, Biostatistics, or related field.
• Minimum of 4 years of experience in Data Science, Statistical Programming, or Clinical Analytics.
• Proficiency in R, SAS, and Python for data analysis and application development.
• Experience with Git, GitHub, and GitHub Actions for collaborative development workflows.
• Strong skills in developing dashboards, visualizations, and analytical applications using R Shiny.
• Understanding of clinical study data and ability to support study teams effectively.
• Ability to operate independently while collaborating in a cross-functional environment.
• Preferred experience in automating development and quality-control processes.