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Statistician skills for your resume and career

Updated January 8, 2025

6 min read

Quoted Experts

Yingfu (Frank) Li Ph.D.,

Michael Gallaugher Ph.D.

Below we've compiled a list of the most critical statistician skills. We ranked the top skills for statisticians based on the percentage of resumes they appeared on. For example, 9.0% of statistician resumes contained data analysis as a skill. Continue reading to find out what skills a statistician needs to be successful in the workplace.

15 statistician skills for your resume and career

1. Data Analysis

Here's how statisticians use data analysis:

Managed several projects from start to finish including data gathering, data analysis, statistical modeling, results analyzing and presentation.
Validate data analysis results and analytically identify potential fraud, waste and/or abuse situations in violation of Medicare/Medicaid laws and regulations.

2. Statistical Methods

Here's how statisticians use statistical methods:

Evaluate marketing strategies using cutting-edge statistical methods such as cluster analysis, classification using logistic regression, and analysis of variance.
Implemented modern statistical methods into manufacturing operations, including statistical process control, design of experiments and time series analysis.

3. Statistical Techniques

Here's how statisticians use statistical techniques:

Prepare reports of local area and/or statewide estimates for employment using statistical techniques and trend projections.
Analyzed and interpreted large data sets using statistical techniques such as general linear models

4. Statistical Data

Statistical data is a numerical data collected by censuses and/or survey from respondents, or from administrative sources to be edited, imputed, aggregated, and/or used in the compilation and production of official statistics.

Here's how statisticians use statistical data:

Compare statistical data and compose managerial reports for submission to Territorial Headquarters as well as Divisional department heads.
Prepared various statistical compilations from voluminous statistical data maintained for the FBI's Uniform Crime Reporting Program.

5. Logistic Regression

Logistic regression is a statistical analysis method accustomed to predict a binary outcome based on a set of independent variables. It is utilized in statistical software to know the connection between the dependent variable and one or more independent variables by estimating probabilities employing a logistic regression equation.

Here's how statisticians use logistic regression:

Design, develop and maintain logistic regression models for Genome-wide association study.
Developed a Logistic Regression Model that created a better/efficient University recruitment process.

6. Research Projects

Here's how statisticians use research projects:

Act as consultant for several performance improvement, evidence-based and research projects and advise Investigators on appropriate statistical methodology.
Document statistical methodology used in a variety of research projects.

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7. Experimental Design

Experimental design is the process of researching in an objective and controlled manner to maximize precision and draw specific conclusions about a hypothesis statement. It is a concept used to efficiently organize, conduct, and interpret the results of experiments to ensure that as much useful information as possible is obtained by conducting a small number of trials. This minimizes the effects of the variables to increase the reliability of the results.

Here's how statisticians use experimental design:

Constructed R packages to deliver statistical estimates for analysis of data from experimental designs common in agricultural research.
Participated extensively in the hypothesis generation, experimental design, protocol planning and study organization process.

Select Skills To Add To Your Resume

Data Analysis

Statistical Methods

Statistical Techniques

Statistical Data

Logistic Regression

Research Projects

8. Python

Python is a widely-known programming language. It is an object-oriented and all-purpose, coding language that can be used for software development as well as web development.

Here's how statisticians use python:

Perform data preprocessing and quality control by R and Python scripts.
Developed SPSS and Python scripts to automate the pre merge/purge process which greatly simplified the workflow process and eliminated costly errors.

9. Data Collection

Data collection means to analyze and collect all the necessary information. It helps in carrying out research and in storing important and necessary information. The most important goal of data collection is to gather the information that is rich and accurate for statistical analysis.

Here's how statisticians use data collection:

Collaborate with scientists to plan meaningful experiments and data collection using SAS in early stage formulation and manufacturing unit process development.
Implemented procedures to optimize data collection and analysis across business units to include continuous feedback to upstream process business owners.

10. Statistical Software

Statistical software is a specialized computer program used for statistical analysis of data collection, organization, analysis, interpretation, and presentation to provide scientific information on patterns and trends.

Here's how statisticians use statistical software:

Developed 2 Statistical Software - DataSwapper and Frontier Visualizer in Java.
Developed and implemented analysis plans using SAS statistical software.

11. Regression

Here's how statisticians use regression:

Conducted statistical analysis including sampling, multivariate analysis, factor analysis, time-series modeling, regression and logistic analysis.
Utilized statistic methods which included: regression/prediction/survival analysis, trend test, logistic/simple regression, and risk factor.

12. Java

Java is a widely-known programming language that was invented in 1995 and is owned by Oracle. It is a server-side language that was created to let app developers "write once, run anywhere". It is easy and simple to learn and use and is powerful, fast, and secure. This object-oriented programming language lets the code be reused that automatically lowers the development cost. Java is specially used for android apps, web and application servers, games, database connections, etc. This programming language is closely related to C++ making it easier for the users to switch between the two.

Here's how statisticians use java:

Collaborate with Java developers, SAS architects and other statistician.
Write JAVA and VBA programs to help out partner teams (e.g.

13. Patients

Here's how statisticians use patients:

Develop method to analyze risk-adjusted, standardized 30-day episode care payment for surgical patients.
Schedule appointments for patients based on desired clinic location and medical provider.

14. 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 statisticians use data management:

Provided guidance and statistical consultation within the department on clinical protocols, data management procedures, and clinical studies.
Work with clinical study and data management personnel to assure the data quality and accuracy for statistical analyses.

15. 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 statisticians use study design:

Provide epidemiological statistical expertise in research methodology and study design, and analysis plan for observational studies and clinical trials.
Contributed to avionic failure analysis predictions and development programs & study designs for improvement.

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What skills help Statisticians find jobs?

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

What skills stand out on Statistician 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 Statisticians 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.

What hard/technical skills are most important for Statisticians?

Michael Gallaugher Ph.D.

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

With the types of data being analyzed today, computational and coding skills are key. Anyone entering the statistics field, regardless of going into academia or industry, should be comfortable coding in at least one statistical computing language such as R, python, or more recently, Julia. In addition, and this is probably obvious, strong mathematical skills are also very important.

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

Bernd Schroeder

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 type of skills will young Statisticians 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 statistician skills to add to your resume

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

Data Analysis
Statistical Methods
Statistical Techniques
Statistical Data
Logistic Regression
Research Projects
Experimental Design
Python
Data Collection
Statistical Software
Regression
Java
Patients
Data Management
Study Design
R
Sample Size

Visualization
SPSS
DOE
Clinical Trials
Predictive Models
Statistical Support
PowerPoint
Statistical Models
Technical Reports
Survival Analysis
Statistical Analysis
Data Entry
JMP
Analyze Data
MATLAB
Survey Data
Basketball Games

Process Control
Data Quality
Regression Analysis
Analysis Results
Medicare
SAS/SQL
FDA
Minitab
Linear Regression
Descriptive Statistics
Statistical Reports
Clinical Studies
Statistical Programs
Time Series Analysis
Econometrics

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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