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Data Analytics Virtual Internship Jobs in Dallas, TX

TrinityRail

Data Analytics Intern

Dallas, TX · On-site

Trinity Industry is looking for Data Analytics Interns for our office in Dallas, TX . This position will focus on building, deploying, and scaling agentic AI applications and automated workflows ...

Trinity Industries

Data Analytics Intern

Dallas, TX · On-site

Trinity Industry is looking for Data Analytics Interns for our office in Dallas, TX . This position will focus on building, deploying, and scaling agentic AI applications and automated workflows ...

Cliftonlarsonallen

Data Analyst Senior

Dallas, TX · On-site +1

$107K - $155K/yr

Together with the Data Analytics team, support the building and implementing of solutions for ... Interaction with others will primarily be virtual with leadership and colleagues from other offices.

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Data Analytics Virtual Internship information

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$41

How much do data analytics virtual internship jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for data analytics virtual internship in Dallas, TX is $22.26, according to ZipRecruiter salary data. Most workers in this role earn between $17.12 and $24.23 per hour, depending on experience, location, and employer.

What is a data analytics virtual internship?

A Data Analytics Virtual Internship is a remote learning experience where participants gain practical skills in analyzing and interpreting data using digital tools, often from home or any location with internet access. Interns work on real-world projects, such as data cleaning, visualization, and reporting, to develop their analytical and technical abilities. These internships typically involve using software like Excel, SQL, Python, or Tableau, and may include mentorship or feedback from industry professionals. Virtual internships offer flexibility, making them accessible to students and career changers worldwide. They are a great way to build experience and enhance your resume in the field of data analytics.

What are the key skills and qualifications needed to thrive as a data analytics virtual intern?

To thrive as a Data Analytics Virtual Intern, you need a solid understanding of statistical analysis, data manipulation, and foundational programming skills, often gained through coursework in data science or related fields. Familiarity with tools like Excel, SQL, Python, and data visualization platforms such as Tableau is typically required. Strong attention to detail, effective communication, and self-motivation help interns stand out when working remotely and collaborating on projects. These skills ensure interns can analyze data accurately, deliver actionable insights, and contribute meaningfully to virtual teams.

What types of real-world projects can I expect to work on during a data analytics virtual internship?

During a Data Analytics Virtual Internship, you can expect to work on projects such as analyzing business datasets, creating dashboards and visualizations, performing data cleaning, and generating actionable insights to support decision-making. These projects often simulate challenges faced by data analysts in various industries, helping you build practical experience with tools like Excel, SQL, or Tableau. You may also collaborate remotely with other interns or mentors, receive feedback on your work, and present findings, all of which mirror typical professional workflows.

What is the difference between Data Analytics Virtual Internship vs Data Analyst?

AspectData Analytics Virtual InternshipData Analyst
CredentialsOften students or entry-level with coursework in data analysisTypically requires a degree in data science, statistics, or related field
Work EnvironmentRemote, project-based, temporaryFull-time or part-time, in-office or remote
Employer & Industry UsageInternships offered by companies for training; industry-wideFull-time roles in various industries like finance, healthcare, tech

The main difference is that a Data Analytics Virtual Internship is a temporary, training-focused opportunity for beginners or students, often remote, while a Data Analyst is a full-time professional role requiring more experience and credentials. Internships serve as a stepping stone into the industry, whereas data analyst positions involve ongoing responsibilities and career development.

What are popular job titles related to Data Analytics Virtual Internship jobs in Dallas, TX?

For Data Analytics Virtual Internship jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Data Analytics Virtual Internship jobs in Dallas, TX look for?

The top searched job categories for Data Analytics Virtual Internship jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Data Analytics Virtual Internship jobs?

Cities near Dallas, TX with the most Data Analytics Virtual Internship job openings:

Data Analytics Virtual Internship jobs near you
Infographic showing various Data Analytics Virtual Internship job openings in Dallas, TX as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $46,305 per year, or $22.3 per hour.

Data Analytics Intern

TrinityRail

Dallas, TX • On-site

Part-time

Re-posted 21 days ago

TrinityRail rating

6.3

Company rating: 6.3 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

139th of 175 rated vehicle equipment hire

Job description

Trinity Industry is looking for Data Analytics Interns for our office in Dallas, TX. This position will focus on building, deploying, and scaling agentic AI applications and automated workflows across the enterprise. You will contribute to producing AI-first solutions using large language models, agent frameworks, and AI-assisted coding to deliver deployable apps, agents, automated workflows, and AI orchestration.
This role will provide valuable experience working with state-of-the-art enterprise platforms (Databricks and Palantir Foundry) and AI tools (pro licenses for Codex and Claude Code). The role offers hands-on mentorship from senior analytics professionals, exposure to production data and governance practices, and high visibility to business owners giving you real ownership of high-impact projects.
What You'll Do:
  • Design, prototype, and deliver agentic systems that plan and execute multi-step business tasks.
  • Build automated workflows and connectors that integrate internal systems and APIs.
  • Implement LLM-based agents (prompting, tool-calling, memory, monitoring) and harden prototypes for handoff.
  • Produce code and deployable artifacts using AI-assisted generation.
  • Collaborate with data analysts, data scientists, and data engineers as well as stakeholders to gain in-dept knowledge of business problems and likely solutions.
  • Demo results and deliver concise handoff docs, runbooks, and impact metrics.

Qualifications
What You'll Have:
  • Master's or PhD candidate or recent graduate in Data Science, Machine Learning, Computer Science, Applied Math, Statistics, Operations Research, or similar quantitative field.
  • Demonstrable experience building AI prototypes or agentic projects (coursework, research, personal projects, or employment).
  • Generate, test, and iterate code (examples: Python, JavaScript, YAML) using an IDE (VS Code, JetBrains, etc.) with AI-assisted coding (GitHub Copilot, OpenAI Codex,
  • Claude Code, Cursor, or similar). Manual coding fluency is helpful but not mandatory.
  • Familiarity with SQL and cloud data platforms (Databricks, Azure, AWS, or equivalent).
  • Strong problem solving and communication skills; ability to present technical work to nontechnical stakeholders.
Preferred / Nice-to-Have
  • Practical experience with model deployment and monitoring basics (packaging/deploying prototypes, logging/observability, basic cost and drift checks).
  • Experience building or working with data/workflow pipelines or orchestration tools or familiarity with the concepts of scheduling and task orchestration.
  • Experience working with unstructured text and retrieval approaches (RAG or index + LLM patterns) for document/question answering.
  • Comfortable integrating services via REST APIs and using secure authentication patterns.

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