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Data Analysis Intern Jobs in Springfield, VA (NOW HIRING)

As a Data Analyst Intern, you will have the opportunity to work closely with our dedicated team ... Providing support for data analysis and reporting activities * Assisting in collecting, cleaning ...

BD & AI Analysis Intern

Fairfax, VA · On-site

$20 - $22/hr

Everforth ECS is seeking a BD & AI Analysis Intern to work hybrid in our Fairfax, VA office. ECS ... B achelor's degree in Economics, Data Sciences, Business, Management Information Systems, History ...

The Data Center Technician Intern will assist with the installation of cabling systems, cable containment infrastructure, cable replenishment activities, equipment delivery, receiving, and white ...

The Data Center Technician Intern will assist with the installation of cabling systems, cable containment infrastructure, cable replenishment activities, equipment delivery, receiving, and white ...

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Data Analysis Intern information

See Springfield, VA salary details

$12

$23

$43

How much do data analysis intern jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for data analysis intern in Springfield, VA is $23.51, according to ZipRecruiter salary data. Most workers in this role earn between $18.08 and $25.62 per hour, depending on experience, location, and employer.

What are some common challenges faced by Data Analysis Interns during their internship, and how can they overcome them?

Data Analysis Interns often encounter challenges such as working with large, unstructured datasets and learning to use new analysis tools or programming languages. Navigating ambiguous project requirements and balancing multiple deadlines can also be difficult. To overcome these obstacles, interns are encouraged to proactively communicate with their mentors, seek feedback regularly, and make use of available resources such as online tutorials or internal documentation. Collaborating with teammates and asking questions fosters learning and helps interns efficiently resolve roadblocks.

What is the difference between Data Analysis Intern vs Data Analyst?

AspectData Analysis InternData Analyst
Required CredentialsTypically pursuing or recent graduate in related fieldBachelor's or higher in data-related field, some certifications
Work EnvironmentInternship setting, entry-level tasks, supervisedFull-time role, more independent responsibilities
Employer & Industry UsageInternships in various industries, educational focusEstablished roles in finance, tech, healthcare, etc.
Common Search & Comparison IntentUnderstanding entry-level opportunities, learning rolesCareer progression, skill requirements

The main difference between a Data Analysis Intern and a Data Analyst lies in experience, responsibilities, and employment status. Interns are usually students or recent graduates gaining initial exposure, while Data Analysts are full-time professionals handling more complex tasks independently. Internships serve as stepping stones toward becoming a full Data Analyst.

What Do Data Analysis Interns Do?

A data analysis intern supports a data analyst while obtaining valuable practical experience to pursue a position in the field. Your responsibilities in this position include delivering data, formatting information, querying databases for sales, marketing, accounting, and other departments, developing and updating reports, and assisting with projects when needed. Your duties also include evaluating analysis systems, collaborating with other teams, responding to requests for analysis, and investigating data discrepancies. You collect information and review the model to offer recommendations.

What does a Data Analysis Intern do?

A Data Analysis Intern assists in collecting, processing, and interpreting data to help organizations make informed decisions. They often use tools like Excel, SQL, or Python to analyze datasets, create visualizations, and generate reports. Interns work under the supervision of experienced data analysts or data scientists, learning to apply statistical techniques and solve real-world business problems. This role provides hands-on experience in data analytics and helps interns develop valuable technical and analytical skills.

What are the key skills and qualifications needed to thrive as a Data Analysis Intern, and why are they important?

To thrive as a Data Analysis Intern, you should have a solid understanding of statistics, data management, and analytical thinking, often supported by coursework in mathematics, statistics, or a related field. Familiarity with tools like Excel, SQL, Python, or R, as well as data visualization platforms such as Tableau or Power BI, is typically expected. Attention to detail, problem-solving abilities, and effective communication help interns interpret data accurately and present insights clearly. These skills are vital for transforming raw data into actionable insights that support business decision-making.
What are the most commonly searched types of Data Analysis jobs in Springfield, VA? The most popular types of Data Analysis jobs in Springfield, VA are:
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What cities near Springfield, VA are hiring for Data Analysis Intern jobs? Cities near Springfield, VA with the most Data Analysis Intern job openings:
Infographic showing various Data Analysis Intern job openings in Springfield, VA as of July 2026, with employment types broken down into 83% Full Time, 14% Part Time, and 3% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $48,893 per year, or $23.5 per hour.
WBG Pioneer - Geospatial Data Analysis Intern

WBG Pioneer - Geospatial Data Analysis Intern

The World Bank Group

Washington, DC • On-site

Other

Posted 7 days ago


Job description

The Trade Policy and Facilitation Unit is developing a quantitative spatial model to assess the spatial economic impacts of logistics infrastructure, logistics and trade facilitation policies, and trade policies at the national and regional levels. Building on a cities spatial model developed jointly by the International Growth Centre (IGC) and the World Bank, the unit intends to extend this framework beyond the city level and to develop it in partnership with the Development Economics (DEC) group, the Transport global practice, and external partners. The model is intended to complement the unit's existing computable general equilibrium (CGE) analysis. 

This work also builds on a long tradition of World Bank analysis of the sub-national geography of trade, including work on lagging regions and their connection to global markets, and seeks to capture the substantial methodological and data advances that have emerged since. Robust spatial analysis of this kind depends critically on the assembly, cleaning, and structuring of high-quality geospatial data used to parameterize and run the model. 

The intern will support this effort within the Trade Policy and Facilitation Unit, contributing to the compilation and preparation of geospatial datasets and to the operation of the quantitative spatial model, under the supervision of the project team. 

Duties and Responsibilities 

Under the guidance of the project lead, the intern will: 

Compile, clean, and structure the geospatial data required to parameterize and run the quantitative spatial ("cities") model, extending it from the city level to the national and regional levels. 

Assemble and process key spatial inputs - including road and transport networks, population grids, terrain data, port and trade-node locations (e.g., PortWatch), and travel-time layers - into model-ready formats. 

Run the spatial model with the prepared data to assess the spatial economic impacts of logistics infrastructure, trade facilitation measures, and trade policies, in coordination with DEC, Transport, and external partners. 

Construct population-weighted accessibility and remoteness indicators to key trade nodes and correlate them with granular socio-economic data. 

Produce maps, interactive dashboards, and other visual outputs to support diagnostics, model validation, and dissemination. 

Contribute to note writing, presentations, and other analytical and dissemination products, and document data sources, methods, and code for reproducibility.