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Data Analytics Intern Jobs in Texas (NOW HIRING)

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 ...

Zello Inc

Analytics Intern

Austin, TX · On-site

You'd join the Data & AI team in Austin, reporting to our Head of Analytics, and spend the fall fixing that for the reports and topics people use most. This is real ownership, not shadowing. You'll ...

New

Copart, Inc.

Data Engineering Intern

Dallas, TX · On-site

The Data Engineer Intern will be part of the Data Engineering Team. The Data Engineering team works ... BI/Analytical Tool Preferred: Tableau, Pentaho, PowerBI #LI-MS1 #LI-MS1 At Copart, we are focused ...

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Data Analytics Intern information

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$11

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How much do data analytics intern jobs pay per hour?

As of Aug 2, 2026, the average hourly pay for data analytics intern in Texas is $20.97, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $22.84 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.

What are the most commonly searched types of Data Analytics jobs in Texas? The most popular types of Data Analytics jobs in Texas are:
What are popular job titles related to Data Analytics Intern jobs in Texas? For Data Analytics Intern jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Data Analytics Intern jobs in Texas look for? The top searched job categories for Data Analytics Intern jobs in Texas are:
What cities in Texas are hiring for Data Analytics Intern jobs? Cities in Texas with the most Data Analytics Intern job openings:
Data Analytics Intern jobs near you
Infographic showing various Data Analytics Intern job openings in Texas as of July 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $43,610 per year, or $21 per hour.

Data Analytics Intern

TrinityRail

Dallas, TX • On-site

Part-time

Re-posted 15 hours ago

TrinityRail rating

6.3

Company rating: 6.3 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

136th of 171 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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