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Internship Data Science R Jobs in Washington, DC

... data science, analytics, or machine learning in support of intelligence or defense missions. • Proficiency in Python, R, and SQL, and experience with data visualization tools such as Power BI or ...

Data Scientist, Lead

Washington, DC · On-site

$85K - $201.33K/yr

The successful candidate should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and ...

The successful candidate should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and ...

Write either R or Python scripts to drive data science work: flows, have experience using SQL, and managing and merging of disparate data sources, preferably through R, Python or SQL; statistical ...

Responsibilities : • Develop data analytics products, AI services, and enterprise data science ... in Python, R, and/or Scala. • Must be able to obtain or have an Active Secret (or higher ...

Responsibilities : • Develop data analytics products, AI services, and enterprise data science ... in Python, R, and/or Scala. • Must be able to obtain or have an Active Secret (or higher ...

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

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 ...

... or R. * Possesses knowledge and experience of advanced analytics and data storage.Demonstrated oral and written communication skills. * Knowledge of various data science applications and ...

Sr. Data Scientist

Washington, DC · On-site

$103K - $240.07K/yr

The successful candidate should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and ...

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

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 ...

... 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 ...

The successful candidate should be skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and ...

... science or a related field * Strong proficiency in programming languages such as Python or R ... Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)

Reviews and defines requirements for data science cybersecurity approaches. Tools used to include the following or equivalent: AWS, Spark, Kafka, Tableau, Python (e.g., TensorFlow and PyTorch), R (e ...

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Internship Data Science R information

See Washington, DC salary details

$13

$25

$47

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

As of May 31, 2026, the average hourly pay for internship data science r in Washington, DC is $25.49, according to ZipRecruiter salary data. Most workers in this role earn between $19.62 and $27.79 per hour, depending on experience, location, and employer.

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 types of projects can I expect to work on during a Data Science Internship at 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 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 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 are the most commonly searched types of Data Science R jobs in Washington, DC? The most popular types of Data Science R jobs in Washington, DC are:
Infographic showing various Internship Data Science R job openings in Washington, DC as of May 2026, with employment types broken down into 43% Internship, 43% Full Time, and 14% Part Time. Highlights an 65% In-person, 21% Hybrid, and 14% Remote job distribution, with an average salary of $53,016 per year, or $25.5 per hour.
Data Scientist

Data Scientist

ANSER

Reston, VA • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Job Summary:
ANSER enhances national and homeland security by strengthening public institutions, and they are seeking a Data Scientist to advance analytic efficiency and predictive capabilities across the Object-Based Intelligence (OBI) enterprise. The role involves leveraging data science, machine learning, and statistical techniques to analyze and visualize complex multi-INT datasets, delivering actionable insights that support OBI analytic production and decision-making.
Responsibilities:
• Design, develop, and evaluate advanced algorithmic intelligence, data science, and AI techniques to support Object-Based Intelligence (OBI) through all-source analytic tradecraft, assessments, production, and dissemination.
• Propose and apply advanced statistical, mathematical, and experimental methodologies to identify alternatives, formulate models, and develop innovative analytic techniques.
• Research, prototype, and evaluate technologies that augment or automate all-source analytic processes using computer models and advanced analytics.
• Leverage novel technologies (e.g., large language models, NLP, machine learning) to automate and enhance ontologies, entity recognition, extraction, and summarization in accordance with analytic tradecraft standards.
• Develop, refine, and optimize semantic data retrieval and reasoning across knowledge graphs using query languages and protocols (e.g., SPARQL, GraphQL, SHACL, SQL).
• Evaluate data science, AI, and analytic methods for bias, risk, limitations, and potential distortion of analytic conclusions, and support responsible AI practices.
• Execute Test, Evaluation, Verification, and Validation (TEVV) protocols to assess system performance, robustness, fairness, and tradecraft compliance in all-source analysis contexts.
• Develop, track, analyze, and interpret qualitative and quantitative performance metrics to identify trends, gaps, and opportunities for system improvement.
• Collaborate with stakeholders to implement data-driven decision-making processes and best practices for system development, testing, deployment, and continuous improvement.
• Develop and refine methodologies for evaluating analytic systems, including validation, reasoning completeness, coverage, consistency, and fairness.
• Use data engineering, mining, exploratory, predictive, statistical, and scientific techniques to correlate data and produce graphical, written, visual, and verbal analytic products.
• Write and maintain Python or R scripts, use SQL, manage and merge disparate data sources, and develop scalable workflows for large, spatial, and multi-INT datasets.
• Create and operate in distributed analytic environments, scaling algorithms to handle datasets exceeding system memory constraints.
• Work with ambiguous and complex information by deconstructing key questions, exploiting APIs and spatial data, suggesting methodologies, and developing data schemas.
• Provide consultation, governance guidance, documentation review, audit findings, and version-controlled code contributions to advance OBI standards, knowledge modeling, and DIA analytic capabilities.
Qualifications:
Required:
• TS/SCI with CI Poly clearance
• Bachelor’s degree in in Data Science, Computer Science, Statistics, Mathematics, or related technical field.
• Eight or more years of experience in data science, analytics, or machine learning in support of intelligence or defense missions.
• Proficiency in Python, R, and SQL, and experience with data visualization tools such as Power BI or Tableau.
• Demonstrated understanding of Object Based Intelligence frameworks.
• Demonstrated experience with predictive modeling, data mining, statistical analysis, and ML algorithms.
• Familiarity with knowledge graphs, semantic data modeling, and query languages (e.g., SPARQL, GraphQL).
• Experience developing, implementing, and evaluating AI/ML models for analytic efficiency and tradecraft compliance.
• Experience with large data multi-INT analytics, machine learning (ML), and automated predictive analytics.
• Skilled in data visualization and use of graphical applications, including Microsoft Office (Power BI) and Tableau; major data science languages, such as R and Python; managing and merging of disparate data sources, preferably through R, Python, or SQL; statistical analysis; and data mining algorithms.
Preferred:
• Experience supporting DIA, IC, or DoD analytic modernization or OBI initiatives.
• Knowledge of TEVV methodologies, bias detection, and fairness analysis for AI systems.
• Experience with distributed data processing, cloud-based analytics, or large-scale machine learning architectures.
• Knowledge of DoD 8570/8140 compliance and responsible AI policy frameworks.
• Working with in support of Defense Intelligence All-source Analytic Enterprise (DIAAE) OBI efforts, the Defense Intelligence Enterprise Knowledge Model (DIEKM), and Defense Intelligence Core Ontology (DICO).
• Developing OBI governance and tradecraft to assist DIA and other DIAAE organizations conducting OBI.
Company:
In 1958 the Air Force needed a technically qualified unbiased organization that could rapidly provide analysis for identified and evolving mission requirements. Founded in 1958, the company is headquartered in Falls Church, USA, with a team of 501-1000 employees. The company is currently Late Stage.