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Data Analytics Intern Jobs (NOW HIRING)

$29.90/hr

As an AI and Data Analytics Intern, you will work closely with our Sr. Data Analyst and our IT Project Manager to gain hands-on experience in data analytics, machine learning, and technology ...

Energy Analytics Intern

Hartford, CT · On-site

$17 - $22/hr

The Energy Analytics Intern will support operations with energy supply contract management and utility data management for Bridge Energy clients. The individual will be responsible for collecting ...

Energy Analytics Intern

Hartford, CT

$17 - $22/hr

The Energy Analytics Intern will support operations with energy supply contract management and utility data management for Bridge Energy clients. The individual will be responsible for collecting ...

We are seeking an Intern - Analytics to join our corporate office located in Jacksonville, Florida ... Familiarity with data visualization tools such as Power BI * Proficient in SQL Server with ...

$17 - $22/hr

The Energy Analytics Intern will support operations with energy supply contract management and utility data management for Bridge Energy clients. The individual will be responsible for collecting ...

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Data Analytics Intern information

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$12

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How much do data analytics intern jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for data analytics intern in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data analytics intern, and why are they important?

To thrive as a Data Analytics Intern, you need a solid understanding of statistics, data analysis, and proficiency in programming languages like Python or R, often supported by coursework in mathematics, computer science, or related fields. Familiarity with data visualization tools (such as Tableau or Power BI), SQL databases, and spreadsheet software is typically expected. Strong analytical thinking, attention to detail, and effective communication skills help interns interpret data and present findings clearly. These skills are crucial for drawing meaningful insights from data and supporting decision-making processes within an organization.

What are some common challenges data analytics interns face during their internship, and how can they overcome them?

Data Analytics Interns often encounter challenges such as working with large and complex datasets, learning new analytical tools and programming languages on the job, and translating data findings into actionable insights for non-technical stakeholders. To overcome these challenges, interns should proactively seek guidance from mentors, take advantage of available training resources, and communicate regularly with team members to clarify project goals. Developing strong problem-solving skills and being open to feedback also helps interns grow and succeed in the role.

What does a data analytics intern do?

A Data Analytics Intern assists in collecting, processing, and analyzing data to help organizations make informed decisions. They typically work with tools like Excel, SQL, and data visualization software to identify trends, create reports, and support business objectives. Interns often collaborate with data analysts and other team members to gain practical experience and develop their technical skills. Their work may involve cleaning datasets, running basic analyses, and presenting findings to stakeholders.

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

AspectData Analytics InternData Analyst
Required CredentialsTypically pursuing or recent graduate in related fieldBachelor's or higher in data-related field, some certifications
Work EnvironmentInternship programs, entry-level tasks, supervisedFull-time, independent project work, more responsibility
Employer & Industry UsageInternships in various industries, training rolesFull-time roles across industries like finance, tech, healthcare
Common Search & Comparison IntentUnderstanding entry-level opportunities, learning rolesCareer progression, skill development, salary expectations

The main difference between a Data Analytics Intern and a Data Analyst lies in experience, responsibilities, and employment status. Interns are typically students or recent graduates gaining initial exposure, while Data Analysts are full-time professionals handling complex data projects. Internships serve as training grounds, whereas Data Analysts are expected to independently analyze data and contribute to decision-making processes.

Can I do a data analytics intern?

A data analytics intern position is typically available to students or recent graduates with skills in data analysis, statistics, and tools like Excel, SQL, or Python. Applicants usually need to demonstrate analytical abilities and may be required to work part-time or full-time during a specific internship period.
More about Data Analytics Intern jobs
What cities are hiring for Data Analytics Intern jobs? Cities with the most Data Analytics Intern job openings:
What are the most commonly searched types of Data Analytics jobs? The most popular types of Data Analytics jobs are:
What states have the most Data Analytics Intern jobs? States with the most job openings for Data Analytics Intern jobs include:
Infographic showing various Data Analytics Intern job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

WBG Pioneer - Blended Finance Data Analytics Intern

The World Bank Group

Washington, DC

Internship

Posted 23 days ago


Job description

WBG Pioneer

The International Finance Corporation (IFC)is the private sector arm of the World Bank Group and the largest globaldevelopment institution focused exclusively on the private sector in emergingmarkets and developing economies. IFC operates in more than 100 countries andworks with businesses, financial institutions, investors, and governments tocreate jobs and
As part of its strategy, IFC 2030, IFC isstrengthening its role as a platform for private capital mobilization, helpingto address development challenges by crowding in institutional and commercialinvestors at scale.

IFC's work focuses on creating andexpanding markets, supporting private sector growth, and generating sustainableemployment opportunities across key sectors including infrastructure,agribusiness, manufacturing, health, and tourism. Through investment,innovation, partnerships, and blended finance, IFC seeks to acceleratedevelopment impact while supporting job creation and economic resilience.

ThePartnerships & Blended Finance (CBF) Department plays a critical role inadvancing IFC's strategic objectives by mobilizing concessional catalyticcapital and donor resources, managing relationships with bilateral andmultilateral development partners, foundations, philanthropies, and otherstrategic stakeholders, and deploying blended finance solutions that helpde-risk investments and attract private capital into high-impact projects. Thedepartment supports IFC's efforts to expand investment opportunities infrontier and emerging markets, particularly in areas where commercial financingalone is insufficient to address market barriers or perceived risk

ThePortfolio Operations (CBFPO) unit in CBF oversees the integration of blendedfinance and fundraising operations into IFC's systems and processes,strengthens portfolio supervision, improves operational efficiency, andprovides analytics, automation, and reporting.

Duties and Responsibilities

TheBlended Finance Data Analytics Intern will be part of the CBFPO unit and willsupport data analytics, reporting automation, and the development ofdata-driven insights for Blended Finance and fundraising operations.

Contribute to Blended Finance and Fundraising analytics by identifying trends, drivers, performance patterns, and forward-look recommendations to Management.

Apply advanced data analytics, visualization, and AI-enabled techniques to generate insights from Blended Finance and Fundraising data.

Explore opportunities to leverage artificial intelligence (AI), machine learning, and generative AI solutions to improve data quality and data gaps.