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Data Analysis Internship Jobs in Grapevine, TX (NOW HIRING)

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 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 ...

Interns will work in a fast-paced telecom environment shaped by emerging technologies, Network APIs ... Interest in financial analysis, reporting, forecasting, automation, and data-driven decision-making.

An internship with Heidelberg Materials is a unique experience. You'll receive hands-on training ... Investigate data-related issues and assist in root cause analysis and corrective actions * Work ...

An internship with Heidelberg Materials is a unique experience. You'll receive hands-on training ... Investigate data-related issues and assist in root cause analysis and corrective actions * Work ...

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Data Analysis Internship information

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How much do data analysis internship jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for data analysis internship in Grapevine, TX is $20.79, according to ZipRecruiter salary data. Most workers in this role earn between $16.01 and $22.64 per hour, depending on experience, location, and employer.

What is a data analysis internship?

A Data Analysis Internship is a temporary position where students or recent graduates gain practical experience in collecting, processing, and interpreting data to help organizations make informed decisions. Interns typically work under the supervision of experienced data analysts and use tools like Excel, SQL, or Python to analyze datasets. The role helps interns develop technical and analytical skills, and often includes tasks such as generating reports, identifying trends, and presenting findings. This internship is valuable for building a foundation in data analysis and can lead to future career opportunities in the field.

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

To thrive as a Data Analysis Intern, you typically need a strong foundation in statistics, analytical thinking, and familiarity with data manipulation, often supported by coursework in mathematics, computer science, or related fields. Proficiency in tools such as Excel, SQL, Python or R, and data visualization platforms like Tableau is commonly expected. Attention to detail, curiosity, and effective communication skills help interns interpret data accurately and share insights with diverse teams. These abilities are crucial for transforming raw data into actionable insights and supporting informed decision-making within an organization.

What are some common challenges faced during a data analysis internship, and how can I overcome them?

As a Data Analysis Intern, one common challenge is working with large, complex datasets that may have missing or inconsistent information. Learning how to clean and preprocess data efficiently is crucial for meaningful analysis. Another challenge is understanding the business context behind the data, which often requires close collaboration with team members from different departments. To overcome these hurdles, proactively seek guidance from mentors, utilize available documentation, and regularly communicate with stakeholders to clarify project goals and data requirements.

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

AspectData Analysis InternshipData Analyst
Required CredentialsTypically pursuing or recent graduate in related fieldBachelor's or higher in data-related field, some roles prefer certifications
Work EnvironmentInternship programs, entry-level, supervisedFull-time, professional setting, independent responsibilities
Employer & Industry UsageInternship programs in tech, finance, healthcare, etc.Full-time roles across various industries
Search & Comparison IntentLooking for entry-level opportunities, internshipsSeeking full-time data analysis roles

In summary, a Data Analysis Internship is an entry-level, supervised position designed for students or recent graduates to gain experience. A Data Analyst is a full-time professional role requiring more experience and responsibility. Both roles are common in similar industries and often share similar educational backgrounds, but they differ significantly in scope and career stage.

Is a data analysis internship worth it?

A data analysis internship provides practical experience with tools like Excel, SQL, and Python, and helps develop skills in data visualization and reporting. It can improve employability, build a professional network, and often leads to full-time opportunities in data-related roles. The value depends on the internship's quality and how well it aligns with career goals.

What are the most commonly searched types of Data Analysis jobs in Grapevine, TX?

The most popular types of Data Analysis jobs in Grapevine, TX are:

What are popular job titles related to Data Analysis Internship jobs in Grapevine, TX?

For Data Analysis Internship jobs in Grapevine, TX, the most frequently searched job titles are:

What job categories do people searching Data Analysis Internship jobs in Grapevine, TX look for?

The top searched job categories for Data Analysis Internship jobs in Grapevine, TX are:

What cities near Grapevine, TX are hiring for Data Analysis Internship jobs?

Cities near Grapevine, TX with the most Data Analysis Internship job openings:

Data Analytics Intern

Dallas, TX • On-site


Trinity Industries

6.5

Company rating: 6.5 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

410th of 494 rated machine equipment manufacturers

People enjoy working here

Recommended by parents

Respectful managers


Internship

Re-posted 25 days ago


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.

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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