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Statistical analyst skills for your resume and career

Updated January 8, 2025

5 min read

Quoted experts

Stephen A. Matthews Ph.D.,

Michael Gallaugher Ph.D.

Below we've compiled a list of the most critical statistical analyst skills. We ranked the top skills for statistical analysts based on the percentage of resumes they appeared on. For example, 10.8% of statistical analyst resumes contained statistical analysis as a skill. Continue reading to find out what skills a statistical analyst needs to be successful in the workplace.

15 statistical analyst skills for your resume and career

1. Statistical Analysis

Here's how statistical analysts use statistical analysis:

Conducted statistical analysis comparing and contrasting data acquired regarding Worcester State Universities' Diversity initiative versus the Assumption College diversity initiative.
Conducted a complete business system review and executed statistical analysis of financial data to determine current status of local small business.

2. Data Analysis

Here's how statistical analysts use data analysis:

Provide Data analysis which includes working with large pools of data and manipulating information to perform analysis for management.
Provide statistical support in experimental design, data analysis and interpretation as well as manuscript preparation and reporting.

3. Statistical Methods

Here's how statistical analysts use statistical methods:

Performed technology liaison role to ensure systems changes reflected proper statistical methods and resulted in accurate reporting.
Analyzed data sets through various statistical methods and investigated unusual or deficient information to maintain data integrity.

4. Database

A database is a collection of data and information which makes it easy to view, access, and manage. Databases save a lot of time and can store huge amounts of data. Databases make sorting data easier and stores it in certain fields which narrows the searching criteria. A database usually contains tables, graphs, and columns to display data.

Here's how statistical analysts use database:

Created a queuing model database which generated statistical data and probabilities based on customer usage patterns at the Automated Teller Machines.
Corrected and analyzed data records to verify compliance with database rules before loading into warehouse.

5. 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 statistical analysts use data collection:

Reduced warranty by implementing an on-line data collection program for alignment equipment and utilizing engineering trials and analysis.
Research includes primary research collection, in addition to data collection from peer-reviewed medical journal articles.

6. Visualization

Here's how statistical analysts use visualization:

Use data visualization techniques to effectively communicate analytical results and support business decisions.
Use SAS programming and visual analysis with TIBCO Spotfire to create and replicate visualization pages with similar scenarios.

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7. Linear Regression

Here's how statistical analysts use linear regression:

Identified patterns and detected variables leading to increased risk in automobile collisions using simple statistical testing and linear regressions.
Developed non linear regression statistical models of employment practices of John Hancock Life Ins Co using SAS.

8. Regression

Here's how statistical analysts use regression:

Created a number of regression models relating natural gas consumption to daily temperature averages.
Presented paper on regression analysis at the annual American Statistical Society meeting.

9. R

R is a free software environment and a language used by programmers for statistical computing. The R programming language is famously used for data analysis by data scientists.

Here's how statistical analysts use r:

Apply Hypothesis Testing, Time Series models on financial data, accounting data by using R and SAS.
Programmed in R to mine databases for the United States Department of Veterans Affairs (VA).

10. Clinical Trials

Here's how statistical analysts use clinical trials:

Used HTML to design, program, and implement data input screens used in the management of Internet-based medical clinical trials.
Involved in reviewing and providing statistical inputs for Protocol, Clinical Study Reports and Clinical Trial Documents.

11. 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 statistical analysts use statistical data:

Developed, designed, tested and implemented new systems responsible for providing financial information and statistical data to various insurance bureaus.
Compiled and verified premium and loss statistical data for reports to industry regulatory organizations and state regulatory agencies.

12. SPSS

Here's how statistical analysts use spss:

Construct complicated multivariate models to effectively accomplish a particular campaign's financial goal via IBM's Statistical Program SPSS.
Analyzed survey data from 26 program sites in SPSS and Excel for National CORE's spring evaluation.

13. Statistical Models

Here's how statistical analysts use statistical models:

Cooperated with management to develop a new statistical modeling product with summarized credit information;.
Developed a statistical model to simulate vehicular traffic using VISSIM a traffic simulation software.

14. Research Projects

Here's how statistical analysts use research projects:

Served as Database/GUI Designer and Demographic Statistician supporting childhood injury research projects.
Supported litigation and provided statistic for safety research projects

15. 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 statistical analysts use data management:

Re-engineered the data management processes which resulted in complete automation of information storage and retrieval.
Collaborated with data management to assure data quality and consistency.

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What skills help Statistical Analysts find jobs?

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

What skills stand out on statistical analyst resumes?

Stephen A. Matthews Ph.D.

Liberal Arts Professor of Sociology, Anthropology, Demography and Geography Director, Graduate Program in Demography Faculty Director, Graduate Programs in Applied Demography Editor, Spatial Demography Associate Editor, Mathematical Population Studies, Pennsylvania State University

Our program is too broad and complex to answer this in any meaningful way (see my opening paragraph). I hope our Ph.D. graduates have both soft skills (e.g., people skills, communication (writing/speaking), team science/work skills, critical thinking skills) as well as the technical skills (e.g., data analysis, data visualization, data ethics, IRB experience, etc.). As mentioned, I also hope they are flexible and adaptive vis-a-vis other perspectives (interdisciplinary outlook).

What soft skills should all statistical analysts 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 statistical analysts?

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 statistical analyst skills would you recommend for someone trying to advance their career?

Pavel Chernyavskiy Ph.D.

Assistant Professor of Statistics, University of Wyoming

Statisticians with subject-matter expertise tend to be more in-demand, all else being equal. For example, quantitative biologists, statistical geneticists, bioinformaticians, industrial statisticians can all be thought of as "statisticians with subject-matter expertise," at least in my opinion. With that in mind, if an applicant can develop their knowledge of a particular area of application during their gap year, it should help them in the job market.

What type of skills will young statistical analysts 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 statistical analyst skills to add to your resume

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

Statistical Analysis
Data Analysis
Statistical Methods
Database
Data Collection
Visualization
Linear Regression
Regression
R
Clinical Trials
Statistical Data
SPSS
Statistical Models
Research Projects
Data Management
Statistical Techniques

Statistical Reports
Clinical Data
Analyze Data
Macro
PC
Java
PowerPoint
Data Manipulation
Predictive Models
Logistic Regression
Biostatistical
SAS/SQL
VBA
Analysis Results
Data Quality
Descriptive Statistics

Pivot Tables
Survey Data
Financial Reports
Anova
FDA
MATLAB
SAS Macros
Cluster Analysis
Survival Analysis
Analytical Support
Time Series Analysis
Unix
Medicaid
Factor Analysis
Minitab
Data Warehouse

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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