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Internship Data Science R Jobs in Columbia, MD (NOW HIRING)

Build SQL, Python, and R scripts to extract data, run calculations, automate recurring analysis ... Required Qualifications * Bachelor's degree in Data Science, Statistics, Computer Science ...

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

... data science, artificial intelligence or machine learning * Proficiency with tools such as Postgresql/SQL, Python, R, and GitLab * Demonstrated experience with producing analytic insights from large ...

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

What You Get Out of the Internship At Stryker, we believe that developing the next generation of ... The data science intern will help drive proactive and predictive insights that inform strategic ...

New

Showing results 41-60

Internship Data Science R information

See Columbia, MD salary details

$11

$22

$41

How much do internship data science r jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for internship data science r in Columbia, MD is $22.33, according to ZipRecruiter salary data. Most workers in this role earn between $17.16 and $24.33 per hour, depending on experience, location, and employer.

What is an internship data science R?

An Internship Data Science R is a temporary position for students or recent graduates to gain practical experience in data science, with a focus on using the R programming language. Interns typically work under the guidance of experienced data scientists, assisting with data cleaning, analysis, visualization, and possibly building statistical models. This role helps interns develop technical and analytical skills, and provides exposure to real-world data-driven projects, often found in industries like finance, healthcare, or technology.

What types of projects can I expect to work on during an internship data science R?

As a Data Science intern at R, you will typically be involved in projects such as data cleaning, exploratory data analysis, and building predictive models under the guidance of experienced data scientists. You may also contribute to developing data visualizations and presenting insights to stakeholders. Interns often collaborate with cross-functional teams, including software engineers and business analysts, which provides valuable exposure to real-world data challenges and team-based problem solving.

What are the key skills and qualifications needed to thrive as an internship data science R, and why are they important?

To thrive as an Internship Data Science R, you need a solid grounding in statistics, data analysis, and programming with R, typically supported by coursework or a degree in a quantitative field. Familiarity with R packages (like tidyverse, ggplot2), data visualization tools, and version control systems such as Git is often required. Strong problem-solving skills, attention to detail, and effective communication help interns translate data insights into actionable recommendations. These abilities are crucial for supporting data-driven decision-making and contributing meaningfully to project teams in a professional environment.

What is the difference between Internship Data Science R vs Data Analyst Intern?

AspectInternship Data Science RData Analyst Intern
Required SkillsProficiency in R, statistical analysis, data visualizationExcel, SQL, basic statistical knowledge
Work EnvironmentData science teams, research projects, analytics departmentsBusiness units, marketing, finance, or operations teams
Industry UsageTech, finance, healthcare, research institutionsRetail, marketing, consulting, finance

Internship Data Science R focuses on applying R programming for statistical analysis and data modeling, often in research or technical environments. Data Analyst Internships emphasize data cleaning, visualization, and reporting using tools like Excel and SQL. Both roles require analytical skills but differ in technical depth and industry focus.

What cities near Columbia, MD are hiring for Internship Data Science R jobs?

Cities near Columbia, MD with the most Internship Data Science R job openings:

Junior Data Scientist

AITHERAS, LLC

Arlington, VA • On-site

Full-time

Re-posted 15 days ago


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.