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Clinical statistical programmer skills for your resume and career

Updated January 8, 2025
4 min read
Quoted experts
Yingfu (Frank) Li Ph.D.,
Wei-Min Huang
Below we've compiled a list of the most critical clinical statistical programmer skills. We ranked the top skills for clinical statistical programmers based on the percentage of resumes they appeared on. For example, 18.7% of clinical statistical programmer resumes contained macro as a skill. Continue reading to find out what skills a clinical statistical programmer needs to be successful in the workplace.

15 clinical statistical programmer skills for your resume and career

1. Macro

Here's how clinical statistical programmers use macro:
  • Assist statisticians with developing and maintaining analysis database specifications and SAS Macro library.
  • Created reusable macros and extensively used existing macros.

2. Data Management

The administrative process that involves collecting and keeping the data safely and cost-effectively is called data management. Data management is a growing field as companies rely on it to store their intangible assets securely to create value. Efficient data management helps a company use the data to make better business decisions.

Here's how clinical statistical programmers use data management:
  • Collaborated with Clinical, Regulatory, and Data Management colleagues to coordinate collection and reporting of clinical trial results.
  • Performed data management and data analysis for clients using statistical packages SAS and other statistical computer languages.

3. Adam

ADAM software assists leading companies by rendering smart and convenient digital management solutions. This software has proved to be of great importance for retailers and Enterprises working on large scales. The ADAM software offers impeccable features to its users, such as designing and structuring media and delivering it among the team members and advanced systems to help users manage their group tasks very efficiently.

Here's how clinical statistical programmers use adam:
  • Created and validated various specifications for SDTM and ADAM transfer purposes.
  • Designed and wrote productivity macros and programmed 100 Adam QC checks

4. Efficacy

Here's how clinical statistical programmers use efficacy:
  • Combined protocols and generated integrated summaries of efficacy and safety following specifications, SAP, CRF.
  • Determined efficacy of experimental medications and formed reports from statistical data.

5. SAS Programs

Here's how clinical statistical programmers use sas programs:
  • Develop, test and document SAS programs for data manipulation, exploratory data analysis and statistical analysis.
  • Maintained complex and reusable Macros and extensively used existing macros and developed SAS Programs.

6. FDA

The Food and Drug Administration (FDA) is a division of the US Department of Health and Human Services that regulates the production and sale of food, pharmaceutical products, medical equipment, and other consumer goods, as well as veterinary medicine. The FDA is now in charge of overseeing the manufacture of products like vaccines, allergy treatments, and beauty products.

Here's how clinical statistical programmers use fda:
  • Developed programs for Integrated Summary Safety reports for FDA submission.
  • Applied knowledge of clinical and science terminology and used SAS software to analyze clinical data for submission to the FDA.

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7. Analysis Datasets

Here's how clinical statistical programmers use analysis datasets:
  • Generated analysis datasets and developed statistical analysis programs (tables and listings) for clinical study reports.
  • Validated already written specifications for the Analysis datasets.

8. QC

Quality control is a set of instructions or procedures to ensure a manufactured product or a service is up to the highest quality standards. This set of quality control criteria are either defined by the clients or the company itself.

Here's how clinical statistical programmers use qc:
  • Generated Tables, Listings and provide QC check, validation of outputs for Oncology clinical trials.
  • Involved in QC work by independent parallel programming and producing the output.

9. ISE

Here's how clinical statistical programmers use ise:
  • Supported for ISS (TESS and SAE) and ISE regulatory response to assist NDA submission and publication.
  • Designed and implemented data collection and reporting system using CDISC-SDTM CDISC-ADAM and both ISS and ISE reporting systems.

10. Oncology

Oncology is defined as the facet of medicine that deals with cancer. Oncology also deals with the prevention and diagnosis of these diseases. A medical professional who has studied the discipline of oncology is referred to as an ‘oncologist'. An oncologist can further specialize in their discipline and become a medical oncologist, surgical oncologist, or radiation oncologist.

Here's how clinical statistical programmers use oncology:
  • Implemented several macros for the production of standard oncology outputs.
  • Worked mainly on Oncology and Vaccines studies.

11. Clinical Trial Data

Here's how clinical statistical programmers use clinical trial data:
  • Provide statistical analyses of clinical trial data for conference abstracts and presentations.
  • Optimized performance using Data Validation and Data Cleaning on Clinical Trial Data.

12. Data Analysis

Here's how clinical statistical programmers use data analysis:
  • Managed low to moderately complex projects, qualitatively and/or quantitatively analyzing data/information, including exploratory data analysis, graphing and forecasting.
  • Design and implement statistical reporting processes for regular data collection and clinical data analysis.

13. Data Validation

Data validation is the process of reviewing and arranging data for efficient data analysis. Data validation includes checking data accuracy, quality of data source, and identifying the importance or relevance of the data.

Here's how clinical statistical programmers use data validation:
  • Assisted in creating, proofing, and implementing collected data validation specifications.
  • Performed data validation, quality review of programs coded by other programmers using PROC COMPARE and checked for data consistency.

14. CRF

CRF (Chronic Renal Failure) is a long-term condition where the kidney gradually stops functioning. It's the leading cause of other medical conditions like diabetes, cardiovascular diseases, or high blood pressure.

Here's how clinical statistical programmers use crf:
  • Developed specifications for CRF data sets, and specifications and mock-up displays for routine listings, tables and figures.
  • Reviewed protocol, CRF's and Statistical Analysis Plan to recognize unnecessary data entries and to develop SAS program.

15. SAS/GRAPH

Here's how clinical statistical programmers use sas/graph:
  • Produced tables and graphical output for research publication using Base SAS, SAS/Stat, & SAS/Graph.
  • Developed modules that produced user-defined SAS/GRAPH printer drivers and automated graphical output generation.
top-skills

What skills help Clinical Statistical Programmers find jobs?

Tell us what job you are looking for, we’ll show you what skills employers want.

What skills stand out on clinical statistical programmer resumes?

Yingfu (Frank) Li Ph.D.Yingfu (Frank) Li Ph.D. LinkedIn profile

Program Chair of Statistics and Associate Professor of Statistics, University of Houston - Clear Lake

Statistical computing and communication skills

What hard/technical skills are most important for clinical statistical programmers?

Wei-Min Huang

Professor, Lehigh University

Strong mathematical and logical insight, Analytical and formulation skills, Wide-ranging computer skills, Knowing the difference between model-based and data-driven approaches.

What clinical statistical programmer skills would you recommend for someone trying to advance their career?

Bernd SchroederBernd Schroeder LinkedIn profile

Professor, Website

The foundation of mathematics is logical and computational precision. Mathematical results are eternal in that there is no update needed once a result has been shown to be true. Consider Pythagoras' Theorem. It's rather old, but its statement and truth are unchanged, as is its applicability. This logical and computational precision will be of primary importance for as long as human beings practice mathematics, science, as well as have interactions in general. For the future, we need to continually refine our ability to use fundamental skills in mathematics/logic/computations to validate and improve results obtained through complex computations: For example, the computations that underly AI cannot and should not be double checked step-by-step, because they are much too intricate. However, simple test cases can often reveal problems in the system as well as features.

What soft skills should all clinical statistical programmers possess?

Michael Gallaugher Ph.D.

Assistant Professor, Elected Director of The Classification Society, Baylor University

From the beginning, statistics have been very interdisciplinary and have become even more so in recent years. With that comes working with people with various backgrounds, including those who have only a very basic understanding of mathematics and statistics. Therefore, a statistician needs to reduce the mathematical and computational jargon to simple language.
Do you want to know more?
Read more about what experts have to say about clinical statistical programmer

List of clinical statistical programmer skills to add to your resume

Clinical statistical programmer skills

The most important skills for a clinical statistical programmer resume and required skills for a clinical statistical programmer to have include:

  • Macro
  • Data Management
  • Adam
  • Efficacy
  • SAS Programs
  • FDA
  • Analysis Datasets
  • QC
  • ISE
  • Oncology
  • Clinical Trial Data
  • Data Analysis
  • Data Validation
  • CRF
  • SAS/GRAPH
  • Sas Graph
  • Regulatory Submissions
  • Base SAS
  • SAS Macros
  • Cdisc Sdtm
  • Visualization
  • Statistical Analysis Plan
  • Statistical Tables
  • Windows
  • SAS/SQL
  • Summary Tables
  • SAS/STAT
  • Edit Checks
  • Unix
  • SPSS
  • Java
  • NDA
  • Extract Data
  • R
  • Extraction
  • Clinical Study Reports
  • Conditional Statements
  • Phase III
  • Develop SAS
  • Regression
  • Oracle Sql
  • Proc SQL
  • Phase II
  • Statistical Reports
  • Proc Freq
  • HTML
  • SAS/ODS

Updated January 8, 2025

Zippia Research Team
Zippia Team

Editorial Staff

The Zippia Research Team has spent countless hours reviewing resumes, job postings, and government data to determine what goes into getting a job in each phase of life. Professional writers and data scientists comprise the Zippia Research Team.

Updated January 8, 2025

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