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Tidyverse Jobs (NOW HIRING)

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

$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 ...

Cytel

Senior R Statistical Programmer

Cambridge, MA · On-site +1

Strong R data manipulation and analysis skills using standard tidyverse packages * Strong R visualization skills for use in static outputs and dashboards * Experience with developing R packages ...

Socket.dev

Data Scientist

Chantilly, VA · On-site

$100 - $140/hr

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 ...

ERC, Inc

Data Scientist

Huntsville, AL · On-site

$80 - $105/hr

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 ...

Jobtailor

Data Scientist

Raleigh, NC · On-site

$110 - $170/hr

Strong programming skills in Python (PySpark, pandas, NumPy, scikit-learn, statsmodels, XGBoost), R (tidyverse, lme4, glmmTMB, glmnet, mgcv), and SQL for large-scale data analysis. * Experience with ...

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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.

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

Junior Data Scientist

AITHERAS, LLC

Arlington, VA • On-site

$100K - $120K/yr

Full-time

Re-posted yesterday

Job description

Junior Data Scientist / Performance Data Analyst I
Location: Washington, DC / Hybrid / Government Facility as Required
Clearance / Background: U.S. Citizen required; ability to obtain DOJ Public Trust and Secret clearance; active Secret preferred
Experience Level: 1-3 years
Role Summary
The Junior Data Scientist / Performance Data Analyst I supports a federal Management Information System program by helping collect, clean, validate, analyze, and visualize operational and performance data.
This role is ideal for an early-career data scientist with strong Python, R, SQL, Tableau, machine learning, NLP, and statistical analysis skills who is ready to progress from research, healthcare, or academic data work into federal mission analytics.
Key Responsibilities
  • Collect, clean, validate, and analyze structured and semi-structured program data.
  • Build SQL, Python, and R scripts to extract data, run calculations, automate recurring analysis, and reduce manual reporting effort.
  • Develop and maintain Tableau dashboards, visual reports, charts, and performance summaries.
  • Support data quality reviews by identifying anomalies, missing values, inconsistent records, and reporting defects.
  • Assist senior analysts with statistical modeling, machine learning, trend analysis, and performance measurement.
  • Translate complex datasets into clear summaries for non-technical stakeholders.
  • Document data sources, business rules, transformation logic, assumptions, and analytical methods.
  • Support recurring weekly, monthly, quarterly, and ad hoc reporting requirements.
  • Review model outputs and error patterns to recommend improvements to analytical workflows.
  • Collaborate with senior data scientists, program analysts, project managers, and government stakeholders.
Required Qualifications
  • Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Information Systems, Neuroscience, Public Health Analytics, or a related quantitative field.
  • 1-3 years of data science, data analytics, research analytics, BI, or machine learning project experience.
  • Hands-on Python experience using pandas, NumPy, scikit-learn, matplotlib, spaCy, Keras, or similar libraries.
  • 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 dashboard/data visualization experience.
  • Experience with machine learning classification, NLP, model evaluation, or predictive analytics.
  • Ability to inspect model errors, validate outputs, and communicate improvement opportunities.
  • Strong Excel and Microsoft Office skills.
  • Ability to explain technical findings to non-technical stakeholders.
  • U.S. citizenship and ability to obtain required federal suitability/clearance.
Preferred Qualifications
  • Active Secret clearance or prior federal suitability.
  • Experience with federal, public sector, law enforcement, financial, healthcare, biomedical, or large statistical datasets.
  • Experience supporting performance metrics, KPI reporting, operational reporting, or program evaluation.
  • Experience building client-facing dashboards or interactive data applications.
  • Experience with BERT, NLP, unstructured text, topic segmentation, or terminology data.
  • Familiarity with data governance, data privacy, PII handling, CUI, or secure data environments.
  • AWS, Git, Jupyter Notebook, or cloud analytics exposure.
Tools / Technologies
Python, R, SQL, Tableau, Excel, Jupyter Notebook, Git, AWS, pandas, NumPy, scikit-learn, spaCy, Keras, tidyverse, tidymodels, ggplot2, Shiny, NLP, BERT, dashboards, data visualization, statistical modeling.

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