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Mathematical statistician skills for your resume and career

Updated January 8, 2025
4 min read
Quoted experts
Yingfu (Frank) Li Ph.D.,
Michael Gallaugher Ph.D.
Below we've compiled a list of the most critical mathematical statistician skills. We ranked the top skills for mathematical statisticians based on the percentage of resumes they appeared on. For example, 17.6% of mathematical statistician resumes contained statistical methods as a skill. Continue reading to find out what skills a mathematical statistician needs to be successful in the workplace.

15 mathematical statistician skills for your resume and career

1. Statistical Methods

Here's how mathematical statisticians use statistical methods:
  • Investigated statistical methods to determine sample-design parameters, develop data-editing methods, and calculate estimates and standard errors.
  • Applied statistical methods in the area of sample design, variance estimation, coverage evaluation, and imputation.

2. 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 mathematical statisticians use experimental design:
  • Advised drug sponsors on experimental design, sample size and model validity.
  • Supported the non-clinical and clinical scientists with experimental design and statistical analysis and provided the consultation and resolution of business issues.

3. Statistical Models

Here's how mathematical statisticians use statistical models:
  • Developed statistical models to investigate the relationship between stock price and major US macroeconomic variables.
  • Assessed the validity of results, statistical models and conclusions in Final Study Reports.

4. Sample Size

Here's how mathematical statisticians use sample size:
  • Helped with weighting of sample survey data, did sample size calculation when needed.
  • Determined sample sizes and selection procedures for multiple objective surveys.

5. Statistical Research

Here's how mathematical statisticians use statistical research:
  • Worked in the Center for Statistical Research and Methodology as part of the student temporary employment program (STEP).

6. Survey Design

Here's how mathematical statisticians use survey design:
  • Designed, monitored, and implemented several survey design and analysis activities for a variety of establishment-based surveys.Selected Project ExperienceU.S.

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7. DOE

DOE, DOX, or design of experiments is a term used to refer to a part of applied statistics whose main focus is to conduct and observe controlled tests with the ultimate goal of understanding and explaining how information and results might vary under different hypotheses and circumstances and how such variables affect the results and tests. Design of experiments is used in marketing, politics, various sciences, and, of course, experiments.

Here's how mathematical statisticians use doe:
  • Created and delivered custom training in Lean, DFSS, Root Cause Analysis, Systems Thinking, SPC, and DoE.
  • Supported engineering in statistical process control (SPC) and design of experiments (DOE) and root cause analysis.

8. Statistical Analysis

Here's how mathematical statisticians use statistical analysis:
  • Write SAS macros for statistical analysis - t-tests F-test, ANOVA, design of experiments, etc.
  • Perform statistical analysis on data of public health.

9. 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 mathematical 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.

10. Survey Data

Survey Data is characterized as the resultant information that is gathered from an example of respondents that took a review. This information is complete data assembled from an intended interest group about a particular theme to lead research. There are numerous techniques utilized for overview information assortment and factual investigation.

Here's how mathematical statisticians use survey data:
  • Analyzed and summarized survey data.
  • Survey data was collected regarding preference rank ordering of product stimuli alternatives consisting of various combinations of chosen product attribute levels.

11. Computer Programs

A computer program is a set of instructions that can be executed by a computer to perform an operation or task. Computer programs are devised by computer programmers in a programming language. Everything a computer does is through a computer program.

Here's how mathematical statisticians use computer programs:
  • Reviewed and analyzed animal health data and wrote computer programs and professional publications.
  • Designed, developed, tested, implemented, and documented computer programs which were used in the conduction of population surveys.

12. 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 mathematical statisticians use sas:
  • Used SQL to extract needed data from an Oracle Database and used SAS for statistical processing.
  • Received formal training on the use of SAS and other statistical software programs

13. Analyze Data

Analyze data or data analysis refers to the practice of studying, organizing, and transforming data to make it more useful. It also includes the cleansing of non-useful information which helps in better decision making regarding any particular matter. Analyze data is a practice that is used widely in the field of business, social sciences, and science.

Here's how mathematical statisticians use analyze data:
  • Designed methods to analyze data on the effect of moisture content and duration of load on lumber.
  • Utilize various statistical packages to analyze data and create formal reports and recommendations to drive improvement.

14. Sample Design

Here's how mathematical statisticians use sample design:
  • Prepared the Sample Design specification report that outlined the sample design countries should follow when implementing their version of the GATS.
  • Developed the sample design and weighting tasks for various house- and establishment-level studies.

15. BLS

Here's how mathematical statisticians use bls:
  • Selected to support redesign of largest BLS PATC (Professional, Administrative, Technical and Clerical) survey.
  • Received BLS Award for Eminent Achievement.
top-skills

What skills help Mathematical Statisticians find jobs?

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

What skills stand out on mathematical statistician 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 soft skills should all mathematical 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 mathematical 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 mathematical statistician 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 type of skills will young mathematical statisticians need?

Xingye Qiao Ph.D.Xingye Qiao Ph.D. LinkedIn profile

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.
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Read more about what experts have to say about mathematical statistician

List of mathematical statistician skills to add to your resume

Mathematical statistician skills

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

  • Statistical Methods
  • Experimental Design
  • Statistical Models
  • Sample Size
  • Statistical Research
  • Survey Design
  • DOE
  • Statistical Analysis
  • Statistical Data
  • Survey Data
  • Computer Programs
  • SAS
  • Analyze Data
  • Sample Design
  • BLS
  • Statistical Programs
  • Regression
  • R
  • Sample Selection
  • DOD
  • Statistical Support
  • Time Series Analysis
  • FDA
  • Macro
  • Survey Methodology
  • Statistical Tests
  • Database Management
  • CDC
  • Data Analysis Results
  • Data Quality
  • Unix
  • Biometrics
  • Censuses
  • Clinical Trials
  • Response Rates
  • Chronic Disease
  • Survival Analysis

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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