Statistical Programmer II banner
a Statistical Programmer II thumbnail
Statistical Programmer II

Overview, Education, Careers Types, Skills, Career Path, Resources

Statistical Programmers analyze data, develop statistical models, and create reports. They ensure data accuracy and support decision-making through statistical expertise.

Average Salary

₹7,00,000

Growth

high

Satisfaction

medium

Home/Careers/information technology and computer science/statistical programmer ii
Functional Skills

Functional Skills are essential skills that help individuals perform tasks effectively in everyday life, work, and education.

    -
    Statistical Modeling
    -
    Programming Languages (SAS, R, Python)
    -
    Data Management and Manipulation
    -
    Clinical Trial Data Analysis
    -
    Regulatory Compliance (e.g., FDA, EMA)
    -
    Data Visualization
    -
    Statistical Reporting
    -
    Machine Learning
    -
    Database Management
    -
    Version Control (Git)
    -
    Scripting and Automation
    -
    Data Quality Assurance
Soft Skills

Communication, teamwork, and critical thinking to ensure seamless project execution.

    -
    Problem-Solving
    -
    Attention to Detail
    -
    Communication Skills
    -
    Time Management
    -
    Adaptability
    -
    Teamwork and Collaboration
    -
    Critical Thinking
    -
    Leadership Skills
Technical Skills

Technical Skills are specialized abilities and knowledge needed to perform specific tasks or functions.

    -
    SAS Programming
    -
    R Programming
    -
    Python (with Pandas, NumPy, SciPy)
    -
    SQL
    -
    Statistical Modeling
    -
    Data Visualization
    -
    Clinical Data Management
    -
    Machine Learning
    -
    Shell Scripting
    -
    Data Warehousing Concepts
Duties and Responsiblities

Task

95%

Develop and validate statistical programs using SAS, R, or Python to analyze clinical trial data, ensuring accuracy and compliance with regulatory standards.

90%

Create and maintain comprehensive documentation for all statistical programming activities, including specifications, programs, and validation reports.

85%

Collaborate with biostatisticians and clinical data managers to define study endpoints and develop statistical analysis plans (SAPs).

80%

Perform data cleaning, transformation, and integration from various sources to create analysis-ready datasets for statistical modeling.

75%

Generate tables, listings, and figures (TLFs) for clinical study reports (CSRs) and regulatory submissions, adhering to CDISC standards.

70%

Participate in the review and quality control of statistical deliverables to ensure accuracy and consistency across projects.

65%

Implement and maintain standard operating procedures (SOPs) and best practices for statistical programming to improve efficiency and quality.

60%

Provide support for regulatory audits and inspections by preparing documentation and responding to queries related to statistical programming.

Work Activities

95%

Perform advanced statistical analysis using SAS, R, or Python to interpret clinical trial data.

92%

Develop and validate SAS programs for data extraction, transformation, and loading (ETL) processes.

90%

Generate tables, listings, and figures (TLFs) for clinical study reports and regulatory submissions.

88%

Ensure all programming activities adhere to regulatory guidelines (e.g., FDA, EMA) and company SOPs.

85%

Conduct thorough data quality checks to identify and resolve data inconsistencies or errors.

82%

Collaborate with biostatisticians, data managers, and clinicians to define study requirements.

80%

Convert raw clinical data into SDTM and ADaM datasets for regulatory submissions.

78%

Develop and maintain SAS macros to automate repetitive programming tasks.

75%

Create and maintain comprehensive documentation for all programs and analyses.

72%

Apply statistical modeling techniques to analyze clinical trial outcomes.

70%

Integrate data from multiple sources to create comprehensive datasets for analysis.

68%

Identify and implement process improvements to enhance programming efficiency.

Detailed Work Profile

Interests