Statistical Programmer

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Key Accountabilities

The Statistical Programmer is responsible for all statistical programming aspects for research, development, and marketed product needs. This position is a key contributor in terms of supporting data analysis, reporting and publication to meet business-critical and regulatory commitments.

The Statistical Programmer is accountable to:

  1. Lead statistical programming activities at project level.
  2. Co-ordinate activities of all programmers either internally or externally assigned to the study/studies.
  3. Build and maintain effective working relationship with cross-functional teams, able to summarize and discuss status of deliverables and critical programming aspects (timelines, scope)
  4. Review eCRF, discuss data structures and review activities as member of the Data Review Team.
  5. Comply with company, department and CDISC standards and processes, review and develop programming specifications as part of the analysis plans
  6. Ensure timely and quality development and validation of datasets and outputs for CSRs, regulatory submissions/interactions, safety reports, publications or exploratory analyses (as required) in the assigned drug development study/project according to specifications
  7. Responsible for quality control and audit readiness of all assigned statistical programming deliverables as well as accuracy and reliability of statistical analysis results.
  8. Maintain up-to-date knowledge of programming software (e.g. SAS) as well as CDISC requirements (SDTM, ADaM, eCTD, Define.xml), attend functional meetings and trainings.
  9. Develop company SAS macros and utilities.

Complexity:

  1. Knowledge of relevant aspects of therapeutic areas, especially knowledge of oncology and immunology.
  2. Knowledge of statistical methodology.

Specialized Knowledge:

  1. Extensive programming experience in SAS including Data step, Macros, Statistical procedures, and Output delivery system.
  2. Good knowledge of CDISC standards.

Minimum Requirements:

  1. Bachelor or advanced degree in statistics, computer science, mathematics, life sciences or related fields is required.
  2. At least 3-5 years in relevant experience in clinical research with emphasis in the development and support of the analysis of clinical data.

Preferred Requirements:

  1. Working experience in oncology projects.
  2. Experience in performing exploratory analysis to support publication.
  3. Project management experience.