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Data Analytics Intern Jobs in Forney, TX (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 ...

Workiva

Spring 2027 Intern - Data Analytics

Dallas, TX · On-site

$22/hr

The Data Research and Collection Intern collects and interprets data for our customers affected by ... Analyze use of Wdesk by current customers in the EU What You'll Need Minimum Qualifications

Workiva

Spring 2027 Intern - Data Analytics

Dallas, TX · On-site +1

$22/hr

The Data Research and Collection Intern collects and interprets data for our customers affected by ... Analyze use of Wdesk by current customers in the EU What You'll Need Minimum Qualifications

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All JobsData Analytics Intern JobsData Analytics Intern Jobs in Forney, TX

Data Analytics Intern information

See Forney, TX salary details

$10

$20

$37

How much do data analytics intern jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for data analytics intern in Forney, TX is $20.27, according to ZipRecruiter salary data. Most workers in this role earn between $15.58 and $22.07 per hour, depending on experience, location, and employer.

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 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 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 internship?

A data analytics intern internship is typically available to students or recent graduates with skills in data analysis, statistics, and tools like Excel, SQL, or Python. Internships usually have age or educational requirements and may require a resume or interview process. They provide practical experience in data collection, cleaning, and reporting within a professional environment.

What cities near Forney, TX are hiring for Data Analytics Intern jobs?

Cities near Forney, TX with the most Data Analytics Intern job openings:

Data Analytics Intern jobs near you
Infographic showing various Data Analytics Intern job openings in Forney, TX as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $42,168 per year, or $20.3 per hour.

Data Analytics Intern

TrinityRail

Dallas, TX • On-site

Part-time

Re-posted 4 days ago

TrinityRail rating

6.3

Company rating: 6.3 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

141st of 177 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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