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Research Biostatistician skills for your resume and career

Updated January 8, 2025

3 min read

Quoted Experts

Yingfu (Frank) Li Ph.D.,

Paul Bernhardt

Below we've compiled a list of the most critical research biostatistician skills. We ranked the top skills for research biostatisticians based on the percentage of resumes they appeared on. For example, 18.0% of research biostatistician resumes contained sas as a skill. Continue reading to find out what skills a research biostatistician needs to be successful in the workplace.

15 research biostatistician skills for your resume and career

1. SAS

SAS stands for Statistical Analysis System which is a Statistical Software designed by SAS institute. This software enables users to perform advanced analytics and queries related to data analytics and predictive analysis. It can retrieve data from different sources and perform statistical analysis on it.

Here's how research biostatisticians use sas:

Use SAS software performing Probabilistic Record Data Linkage among various programs to obtain addition data elements.
Use SAS/BASE, SAS/STAT, SAS/IML and SAS Macro.

2. Statistical Analysis

Here's how research biostatisticians use statistical analysis:

Assist in problem solving related for issues related to statistical analysis or data management.
Provide statistical analysis for key sections of clinical study reports and various regulatory documents.

3. Study Design

Study design entails a detailed framework of data, methods, pathways, procedures, and operations to solve a research problem's variability. These designs come in different forms for different issues, sectors, and fields and aim to find answers and solutions to issues and questions in specific areas.

Here's how research biostatisticians use study design:

Participate in study design and protocol development; Design statistical section of protocol including sample size calculation and power estimation.
Provide statistical input into study design, randomization and analysis methodologies of clinical trial protocols.

4. Research Projects

Here's how research biostatisticians use research projects:

Performed statistical analyses for quantitative/qualitative research projects.
Conduct moderately complex experimentation including data collection, summary and initial analysis, in support of department research projects and guidelines.

5. Stata

STATA is a statistical software package used for data visualization, manipulation, statistics, and automated reporting. Individuals with experience in using other types of statistical software or a background in data science may find it easier to absorb the concepts of STATA quickly.

Here's how research biostatisticians use stata:

Designed a random and representative sampling plan; performed data cleaning and econometric analysis of findings using Excel and STATA.
Used STATA software to assess our hypothesis and ran an adequate diagnostic test to justify the validity of our models.

6. Clinical Trials

Here's how research biostatisticians use clinical trials:

Display, summarize and analyze the data for clinical trials and QC the results.
Perform analysis of clinical trials.

7. 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 research biostatisticians use data management:

Documented methods and provided quality control of data management.
Work closely with Data Management in order to assure proper database design.

Select Skills To Add To Your Resume

SAS

Statistical Analysis

Study Design

Research Projects

Stata

Clinical Trials

8. Public Health

Here's how research biostatisticians use public health:

Collaborated with clinical microbiologists and state epidemiologists to identify priority MRSA public health needs.
Applied predictive modeling expertise contributing to the development of Public Health Laboratory capacity models for influenza.

9. Mathematics

Here's how research biostatisticians use mathematics:

Attended seminars and lectures on various research topics in mathematics.

10. Power Analysis

Here's how research biostatisticians use power analysis:

Performed Sample Size/Power Analysis for a two-looks adaptive design using EAST 6.4.

11. Survival Analysis

Survival analysis is the statistical branch concerning the modeling of time to events. That is, it measures the expected time taken before events such as mechanical failure or biological death occur. A synonymous engineering theory used is the reliability theory where mean time is used to evaluate operational failure rates.

Here's how research biostatisticians use survival analysis:

Evaluated the effectiveness of new heart therapy drugs using statistical analyses including t-tests, linear regression, survival analysis.
Developed extensive SAS macros to obtain summary data on continuous and dichotomous variables and perform survival analysis.

12. Statistical Methods

Here's how research biostatisticians use statistical methods:

Use multiple statistical methods to analyze and wrote surveillance reports to CDC.
Assist in selected appropriate statistical methods for analysis for ongoing studies for AG-1067 (atherorosclerosis, diabetes).

13. Regression

Here's how research biostatisticians use regression:

Applied advanced statistical methods included but not limited to logistic, regression, non-parametric methods and basic procedures.
Conducted multivariate logistic regression analysis to identify significant factors collectively associated with disease status.

14. IRB

An institutional review board (IRB), is a form of committee that applies research ethics by vetting research procedures to ensure they are ethical. In order to decide whether or not research can be undertaken, they often perform a kind of risk-benefit analysis. The IRB's function is to ensure that adequate safeguards are in place to protect the interests and health of humans who are participants of a research sample.

Here's how research biostatisticians use irb:

Drafted and submitted study protocol documents to IRB, completed required grant regulatory documentation, and assisted with grant application submissions.
Monitor regulatory compliance/audits, IRB submission/amendments, protocol development, maintain source documents, soldier recruitment, consent and clinical interviewing.

15. Statistical Research

Here's how research biostatisticians use statistical research:

Support statistical research by providing advice and contributing to computational aspects.
Conduct statistical research, database management and data analyses for Mississippi Childhood Lead Poisoning Prevention Program.

What skills help Research Biostatisticians find jobs?

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

What skills stand out on Research Biostatistician resumes?

Yingfu (Frank) Li Ph.D.

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

Statistical computing and communication skills

What soft skills should all Research Biostatisticians possess?

Paul Bernhardt

Associate Professor of Statistics, Director of the Applied Statistics Graduate Program, Villanova University

Statisticians generally have to work with a variety of people from a variety of fields. Thus statisticians have to be eager to learn and ask questions. It is common for a client or a scientist consulting with a statistician for the first time to think that they know what they want, but it is the job of the statistician to ask questions to make sure not only that they understand the data and the data-related issues, but that the analyses goals are feasible. In most statistics jobs, working with others, often as a team, is essential. This requires solid communication skills, both in conveying thoughts on the best procedure as well as in explaining technical results to individuals not familiar with statistical jargon.

What hard/technical skills are most important for Research Biostatisticians?

Paul Bernhardt

Associate Professor of Statistics, Director of the Applied Statistics Graduate Program, Villanova University

Statisticians must have a range of methodological knowledge, and which skills are most important will vary heavily from job to job. In some jobs, having experience working with biological data will be most important, and thus particular classwork and methodological skills are most significant. In other cases, statisticians are asked to play a role in designing studies, monitoring data collection, and insuring quality control. Having data analysis skills is very different from knowing experimental design or best survey practices. Most statistics jobs will require expertise in at least one programming language. Pharmaceutical and biostatistics jobs often require knowledge of SAS, whereas finance, business, and other data analysis/science jobs are more likely to require fluency in Python or R. Statisticians who know multiple languages along with database management using SQL are often well-primed for jobs in programming or data science.

What Research Biostatistician skills would you recommend for someone trying to advance their career?

Dr. Robert P. Eyler

Professor, Sonoma State University

Learning to code is a good initial skill, especially if the student sees themselves in a field where databases and the internet of things (IoT) is an important piece of any job they take. Shoring up their skills with Excel if needed is a good way to spend that time too; taking a class on a subject like cybersecurity that is not graded but may help undertsand the strategic landscape of frontier technology businesses may be a good thing to do.

What type of skills will young Research Biostatisticians need?

Xingye Qiao Ph.D.

Associate Professor, Binghamton University

Computing skills are becoming increasingly important, as statistics embraces the data science revolution. Students need to be able to program (using R or Python or some other language), take the data from the web, reshape it, manipulate it to allow easier downstream analysis, and be able to communicate the finding professionally.

All these are, of course, on top of statistical thinking. Competitive student candidates should not only be an order-taker. They should ask hard questions and think about the data problem in the context of the environment that generates the said data. This is related to knowledge of the domains, human contexts, and all kinds of ethical considerations.

Do you want to know more?

List of research biostatistician skills to add to your resume

The most important skills for a research biostatistician resume and required skills for a research biostatistician to have include:

SAS
Statistical Analysis
Study Design
Research Projects
Stata
Clinical Trials
Data Management
Public Health

Mathematics
Power Analysis
Survival Analysis
Statistical Methods
Regression
IRB
Statistical Research
R

Cancer Research
MATLAB
Conference Presentations
Clinical Study Reports
NIH
CRO
Clinical Research Proposals

Updated January 8, 2025

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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