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Junior data analyst skills for your resume and career

Updated January 8, 2025

5 min read

Quoted experts

Dr. Omayra Ortega Ph.D.,

Pavel Chernyavskiy Ph.D.

Below we've compiled a list of the most critical junior data analyst skills. We ranked the top skills for junior data analysts based on the percentage of resumes they appeared on. For example, 11.7% of junior data analyst resumes contained data analysis as a skill. Continue reading to find out what skills a junior data analyst needs to be successful in the workplace.

15 junior data analyst skills for your resume and career

1. Data Analysis

Here's how junior data analysts use data analysis:

Perform Statistical analysis, data profiling, data analysis and documenting different aspects and suggestions for data.
Collaborated with Engineering\Quality\Production digitizing paper logbooks, creating dashboards, and automating quantitative data analysis reports.

2. 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 junior data analysts use python:

Created multiple scripts in Python to perform data manipulation and analysis as well as calculations on energy production and data visualization.
Developed and deployed additional NLP applications (language identification and named entity recognition) with Python and Docker.

3. Visualization

Here's how junior data analysts use visualization:

Involved in System Analysis & Design of the Enterprise Data Visualization Architecture.
Used Tableau Desktop for data visualization & Reporting.

4. Power Bi

Here's how junior data analysts use power bi:

Created multiple data visualization solution for initial Power BI business preview.
Developed Reporting solutions using Power BI.

5. PowerPoint

Here's how junior data analysts use powerpoint:

Produced variance reports, Excel graphs, charts, presentations in PowerPoint.
Identified and communicated new trends to upper level management & presented insights using PowerPoint.

6. 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 junior data analysts use analyze data:

Analyze data from clients and compare it with data warehouse.
Analyze data for accuracy Train new employees Maintain company website Assisted Marketing department

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7. Pivot Tables

A pivot table is a technique used in data processing to arrange and rearrange statistics to prioritize useful information. The aim of a pivot table is to summarize the findings and interpretations of the data extracted. Pivot tables take information from a database or spreadsheet to report sums, average, and other such statistics. This technique is integral to data analysis since it turns the data to view it from different lenses and perspectives.

Here's how junior data analysts use pivot tables:

Interpret qualitative and quantitative data (pivot tables/statistical analyses) and provide high quality graphs, reports, and presentations.
Used Microsoft Excel tools like pivot tables, graphs, charts, solver to perform quantitative analysis.

8. Data Quality

Here's how junior data analysts use data quality:

Developed and implement data collection systems and other strategies that optimize statistical efficiency and data quality.
Created documentation relating to data quality improvement and current project to ensure team consistency.

9. Strong Analytical

Here's how junior data analysts use strong analytical:

Achieved and Maintained strong analytical skills while efficiently utilizing excellent oral and written communication skills.
Maintain strong analytical and problem solving skills, excellent communication and presentation skills.

10. BI

Here's how junior data analysts use bi:

Implemented reports on the Pentaho BI.
Collected and analyzed complex financial/operations data and constructed summary dashboards using BI tool Tableau.

11. 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 junior data analysts use data collection:

Participate in face to face data collection field work (surveys, focus groups, interviews, and observations).
Prepare an accurate data collection and record keeping trackers that present information in clear and logical manner.

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 junior data analysts use sas:

Created and modified existing SAS macros to report summary/descriptive statistics as well as inferential statistics.
Implemented visualizations in SAS to monitor daily project activities.

13. ETL

Here's how junior data analysts use etl:

Designed Data Stage ETL jobs for extracting data from heterogeneous source systems, transform and finally load into the Data Marts.
Assisted ETL team for transformation rules documentation for data migration for OLTP to warehouse for reporting.

14. Statistical Analysis

Here's how junior data analysts use statistical analysis:

Performed advanced statistical analysis on large volumes of data and implemented predictive models to aid in departmental decision making.
Conducted independent statistical analysis, descriptive analysis and logistic regression.

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 junior data analysts use data management:

Ensured that all data management activities are conducted in compliance with relevant regulatory requirements.
Monitored key performance indicators to ensure the integrity of assigned data management areas.

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What skills help Junior Data Analysts find jobs?

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

What skills stand out on junior data analyst resumes?

Dr. Omayra Ortega Ph.D.

Assistant Professor of Mathematics & Statistics, Sonoma State University

Everyone should have some familiarity with basic word processing software, spreadsheets, and some coding. It's impossible to know what coding languages will be in vogue when you are on the job market, but it is important to be familiar with at least one programming language. Most employers will be content that you have experience coding and are willing to learn a new language. The willingness to learn something new is essential. It's always best if you have the skills required for the job that you are applying to, but as the job market changes over time, it is difficult to predict what exactly employers will be looking for once you graduate. A good strategy for students still in school is to make sure that your soft skills are up to par. Leadership skills, the ability to work well in a team, public speaking skills, good writing proficiency, and generally communication skills are essential to every employer.

What junior data 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 junior data analysts need?

Zhixin Wu Ph.D.

Associate Professor, DePauw University

Problem solving skills, analytical skills, self-learning ability, and good communication skills.

What technical skills for a junior data analyst stand out to employers?

Lenny Fukshansky Ph.D.

Professor of Mathematics, Claremont McKenna College

I believe that the industry employers are constantly looking for people with a combination of strong analytic background (including mathematical modeling, statistics, and programming knowledge), good communication skills and leadership potential. We are obviously observing a rapid surge of data science, but it is important to keep in mind that just the familiarity with current data handling techniques is not sufficient for a successful career going forward. This knowledge has to rest on the understanding of fundamental mathematical and computer science apparatus from which data science has emerged. As such, I would recommend a major in mathematics, complemented by some data science courses or a minor.

What soft skills should all junior data analysts possess?

Bertrand Clarke Ph.D.

Professor and Chair, University of Nebraska - Lincoln

Ability to communicate results to the people who want the answers. Ability to outline the method you used and why you used it. Ability to work in a group that has diverse backgrounds. Less tangible, the sixth sense stats people have for how far to push an analysis, e.g., not overuse the data, not make assumptions you can't justify.

What hard/technical skills are most important for junior data analysts?

Bertrand Clarke Ph.D.

Professor and Chair, University of Nebraska - Lincoln

Linear models and their follow-on techniques -- generalized linear models, mixed models. Familiarity with nonlinear methods, including classification. Basic nonparametric techniques like PCA, clustering, etc.

Expertise in programming in various languages (R, Python, SAS, etc.)
Expertise in working with various data structures and software.

There are specialized areas as well -- time series, spatial statistics, etc. But they often rely on the methods in the first paragraph.

Do you want to know more?

List of junior data analyst skills to add to your resume

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

Data Analysis
Python
Visualization
Power Bi
PowerPoint
Analyze Data
Pivot Tables
Data Quality
Strong Analytical
BI
Data Collection
SAS
ETL
Statistical Analysis
Data Management
Data Entry

Database Design
CRM
Data Integrity
VBA
QA
Data Validation
R
Data Warehouse
Data Warehousing
Oracle Sql
SharePoint
Statistical Techniques
Test Cases
PL/SQL
Financial Data
Extraction

Business Stakeholders
KPI
Profiling
Ssis
Unix
HTML
Business Rules
Regression
B Testing
User Acceptance
Teradata
Tableau Desktop
Triggers
T-SQL
Amazon Web Services
Sales Data

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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