Heading

US-TX-Dallas

Internship

Onsite

Intern

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.

Apply Now

Responsibilities

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

Qualification

Required

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

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