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Tidyverse Jobs (NOW HIRING)

Skillify Solutions

Python/R Analyst

Richmond, TX · On-site

Use R packages such as tidyverse, dplyr, ggplot2, and Shiny for analysis and visualization. * Develop dashboards, reports, and visualizations to communicate analytical findings. * Work with SQL ...

AITHERAS, LLC

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

R experience using tidyverse, tidymodels, ggplot2, Shiny, or equivalent packages. * SQL experience for querying, joining, filtering, and preparing datasets. * Tableau, Power BI, R Shiny, or similar ...

AITHERAS, LLC

Junior Data Scientist

Arlington, VA · On-site

R experience using tidyverse, tidymodels, ggplot2, Shiny, or equivalent packages. * SQL experience for querying, joining, filtering, and preparing datasets. * Tableau, Power BI, R Shiny, or similar ...

AT and T

Sr Specialist Data Scientist

Plano, TX · On-site

$132K - $192K/yr

Apply knowledge with modern ML packages and libraries including SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and AutoML tools. REQUIREMENTS: Requires a Bachelor's degree, or ...

AT&T

Sr Specialist Data Scientist

Plano, TX · On-site

$132K - $192K/yr

Apply knowledge with modern ML packages and libraries including SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and AutoML tools. REQUIREMENTS: Requires a Bachelor's degree, or ...

Northwestern University

Statistical Analyst

Evanston, IL · On-site

$70K - $80K/yr

Advanced proficiency in R and R Markdown for data management, analysis, and report generation, including the ability to write clean, well-documented, and reproducible code using the tidyverse and ...

ERC, Inc

Data Scientist

Huntsville, AL · On-site

Deep knowledge of common programming languages (Python, R, Julia), data science packages and frameworks (Pandas, NumPy, Scikit-learn, tidyr, tidyverse). * Background working with common data ...

Socket.dev

Data Scientist

Chantilly, VA · On-site

Tools: AWS, Spark, Kafka, Tableau, Python (TensorFlow, PyTorch), R (tidyverse, RShiny), Splunk, Agile/Scrum/Jira/Confluence preferred. Data Scientist, Level 3 (Senior) * Oversees data science ...

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Tidyverse information

What are Tidyverse packages?

The Tidyverse is a collection of R packages designed for data science. These packages share an underlying design philosophy, grammar, and data structures, making it easy to manipulate, explore, and visualize data. The core Tidyverse packages include ggplot2, dplyr, tidyr, readr, purrr, tibble, stringr, and forcats, among others. They help streamline common data analysis tasks and are widely used by R programmers for efficient and readable code.

What are the key skills and qualifications needed to thrive as a Tidyverse data analyst?

To thrive as a Tidyverse Data Analyst, you need strong data manipulation, visualization, and statistical analysis skills, typically supported by a degree in statistics, data science, or a related field. Proficiency in R programming and mastery of Tidyverse packages (such as dplyr, ggplot2, tidyr, and readr) are essential, along with knowledge of version control systems like Git. Analytical thinking, attention to detail, and clear communication are standout soft skills in this role. These skills ensure accurate data insights, reproducible workflows, and effective collaboration with stakeholders for data-driven decision-making.

How does working as a Tidyverse data analyst typically involve collaboration with other teams or departments?

As a Tidyverse data analyst, collaboration is a core aspect of the role. You'll often work closely with stakeholders from various departments, such as marketing, finance, or product teams, to understand their data needs and translate them into actionable insights using R and the Tidyverse package suite. Regular communication is essential for gathering requirements, presenting findings, and ensuring that analyses align with business goals. Additionally, you may partner with data engineers or IT to access and manage datasets, and with other analysts to share best practices and streamline workflows.

What is the difference between Tidyverse vs Data Analyst?

AspectTidyverseData Analyst
Primary FocusData manipulation, visualization, and analysis using R packagesInterpreting data, creating reports, and supporting decision-making
Skills & ToolsR programming, ggplot2, dplyr, tidyr, readrExcel, SQL, statistical analysis, data visualization tools
Work EnvironmentData science teams, research labs, analytics departmentsBusiness, finance, marketing, healthcare sectors
Required CredentialsKnowledge of R, data analysis, statisticsDegree in statistics, data science, or related fields

While Tidyverse refers to a collection of R packages for data manipulation and visualization, Data Analysts utilize these tools along with other skills to interpret data and generate insights. Tidyverse is a technical toolkit, whereas Data Analyst is a role that applies these tools in various industries to support decision-making.

More about Tidyverse jobs

What cities are hiring for Tidyverse jobs?

Cities with the most Tidyverse job openings:

What states have the most Tidyverse jobs?

States with the most job openings for Tidyverse jobs include:

What job categories do people searching Tidyverse jobs look for?

The top searched job categories for Tidyverse jobs are:

What other helpful pages are available for Tidyverse?

Other pages related to Tidyverse:

Tidyverse jobs near you
Infographic showing various Tidyverse job openings in the United States as of September 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 75% In-person, and 25% Hybrid job distribution.

Python/R Analyst

Richmond, TX • On-site

Skillify Solutions
See more jobs at Skillify Solutionsexternal

Other

Posted 12 days ago

Job description

Job Description

We are looking for an experienced Python / R Data Analyst with 3+ years of hands-on experience in Python, R, data analysis, statistical modeling, and data visualization. The ideal candidate will analyze complex datasets, identify meaningful insights, and work with business and technical teams to support data-driven decision-making.

Key Responsibilities

  • Analyze large and complex datasets using Python and R.
  • Develop data analysis and statistical models to identify trends, patterns, and business insights.
  • Write clean, efficient, and reusable Python and R code for data processing and analysis.
  • Perform data cleaning, transformation, validation, and exploratory data analysis (EDA).
  • Use Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn for data analysis and visualization.
  • Use R packages such as tidyverse, dplyr, ggplot2, and Shiny for analysis and visualization.
  • Develop dashboards, reports, and visualizations to communicate analytical findings.
  • Work with SQL databases to extract and analyze data.
  • Collaborate with business stakeholders, data engineers, and technical teams to understand requirements.
  • Present analytical findings and recommendations to technical and non-technical stakeholders.
  • Ensure data quality, accuracy, and consistency across analytical outputs.

Required Qualifications

  • 3+ years of professional experience with Python.
  • 3+ years of professional experience with R.
  • Strong experience with Pandas, NumPy, Matplotlib, and Seaborn.
  • Strong knowledge of R, Tidyverse, dplyr, and ggplot2.
  • Strong SQL skills and experience working with relational databases.
  • Experience with data cleaning, manipulation, and exploratory data analysis.
  • Strong understanding of statistics and data analysis techniques.
  • Experience creating data visualizations and analytical reports.
  • Strong problem-solving and analytical skills.
  • Excellent communication and stakeholder-management skills.

Preferred Qualifications

  • Experience with Machine Learning and predictive analytics.
  • Experience with Scikit-learn or other Python ML libraries.
  • Experience with R Shiny.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Experience with Tableau or Power BI.
  • Experience working in Agile/Scrum environments.

Apply