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Senior statistician skills for your resume and career

Updated January 8, 2025

5 min read

Quoted experts

Yingfu (Frank) Li Ph.D.,

Michael Gallaugher Ph.D.

Below we've compiled a list of the most critical senior statistician skills. We ranked the top skills for senior statisticians based on the percentage of resumes they appeared on. For example, 9.4% of senior statistician resumes contained statistical methods as a skill. Continue reading to find out what skills a senior statistician needs to be successful in the workplace.

15 senior statistician skills for your resume and career

1. Statistical Methods

Here's how senior statisticians use statistical methods:

Teach statistical methods to research fellows and research associates class.
Provided training for the statistical methods used in TLFs to the CRO programmers under my supervision.

2. Data Analysis

Here's how senior statisticians use data analysis:

Participate on engineering problem solving teams and task forces, leveraging data analysis and interpretation to resolve technical issues.
Work in SAS Enterprise Guide involving data analysis in support of government contracts with CMS to detect suspicious claim billing.

3. Healthcare

Healthcare is the maintenance or improvement of a person's health by the diagnosis and treatment of a person's injury, illness, or any other disease. Healthcare is a basic necessity of human life and is the responsibility of the country's government to ensure that each person gets healthcare. Providing healthcare is the job of certified health professionals that includes doctors, surgeons, nurses, and other physicians. Pharmaceutical companies, hospitals, dentistry, therapy, and health training all come under healthcare. Healthcare plays a vital role in the country's economy and its development.

Here's how senior statisticians use healthcare:

Collaborated with Stanford researchers on a study to identify patient-level factors of healthcare utilization for cancer patients.
Collaborated with physicians, and epidemiologists on healthcare quality improvement projects.

4. 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 senior statisticians use data management:

Coordinate with programmers and data management personnel as to database maintenance, updated and documented.
Created protocol for data management procedure and performed quality assurance monitoring for databases.

5. Clinical Trials

Here's how senior statisticians use clinical trials:

Lead statistician responsible for statistical analysis plan in several reproductive and cardiology clinical trials.
Developed analysis plans and wrote statistical result section of Clinical Trial Report.

6. 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 senior statisticians use study design:

Worked in coordination with lead programmer to provide study design and maintenance of standard programming environment as per the Protocol.
Enhance the study design and increased the validity of the data collected.

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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 senior statisticians use experimental design:

Developed test and experimental designs, performed statistical analysis (SAS), and wrote reports.
Developed and taught a course on experimental design.

8. Statistical Support

Here's how senior statisticians use statistical support:

Provide statistical support for Eli Lilly PR&D and Manufacturing departments and oversight of statistical work from Lilly China site.
Provided statistical support for clinical studies and a study on association between Physicians Pay-Per-Performance and quality of patients' care.

9. Statistical Analysis

Here's how senior statisticians use statistical analysis:

Develop user requirements for Statistical Analysis Modules (generic code templates) used to produce standard statistical analyses and reports.
Conducted ongoing statistical analysis to support management decision making and acted as consultant for internal research projects.

10. 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 senior statisticians use data collection:

Develop sampling strategies and data collection methodologies; perform power analysis and sample size calculations.
Initiated development of a standardized protocol for data collection and database management.

11. 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 senior statisticians use fda:

Served as the lead statistician in NDA submissions to FDA, reviewed clinical modules in CTD.
Provided Survival Updates on 1 oncology drug to the FDA for 2 years after NDA approval.

12. Regression

Here's how senior statisticians use regression:

Employed sophisticated Latent Class Regression Modeling and Latent Clustering Technique to create enterprise level segmentation for all major Sanofi-Aventis brands.
Developed multivariate regression models, factor analysis models, predictive response modeling, and logistic modeling for Abbott Diagnostic Division.

13. 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 senior statisticians 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.

14. Statistical Expertise

Here's how senior statisticians use statistical expertise:

Provided statistical expertise to project and analysis teams.
Provided methodological and statistical expertise to the development of new products.

15. Statistical Techniques

Here's how senior statisticians use statistical techniques:

Consult with investigators and determine appropriate statistical techniques to analyze data.
Use statistical techniques to program and identify potential errors in claims payment, calculate estimated over payments and report overpayments.

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What skills help Senior Statisticians find jobs?

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

What skills stand out on senior 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 senior 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 senior 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 senior 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 senior 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 senior statistician skills to add to your resume

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

Statistical Methods
Data Analysis
Healthcare
Data Management
Clinical Trials
Study Design
Experimental Design
Statistical Support
Statistical Analysis
Data Collection
FDA
Regression
Survival Analysis
Statistical Expertise
Statistical Techniques
Pharmaceutical Industry

Predictive Models
Logistic Regression
Visualization
Research Projects
Statistical Aspects
Statistical Models
NDA
Linear Models
R
Analyze Data
SPSS
Survey Data
Statistical Design
Sample Size Calculations
Macro
Statistical Process Control

Medicare
Clinical Study Reports
Statistical Results
Econometrics
Statistical Tests
Calculation
Statistical Sections
CRO
Regression Analysis
Unix
Sas Jmp
Statistical Reports
Product Development
Study Protocols
Biostatistical
JMP

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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