Trinity Industry is looking for Financial 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 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, with growing application to financial, economic, and operational use cases.

This role targets data-oriented candidates who have a background or are interested in applying financial, quantitative, and economic concepts to real-world assets, cost, and FP&A problems. The role will provide valuable experience working with state-of-the-art enterprise platforms (Databricks and Palantir Foundry), AI tools (pro licenses for Codex and Claude Code), and financial data sources (e.g., Bloomberg). It offers hands-on mentorship from senior quantitative professionals, exposure to production data and governance practices, and high visibility to business owners, giving you real ownership of high-impact projects. Minimum of 20 hours per week.

Key responsibilities:

Design, prototype, and deliver agentic systems that plan and execute multi-step business tasks, including financial, economic, and analytical workflows.

Build automated workflows and connectors that integrate internal systems, APIs, and external financial and macroeconomic data sources.

Enhance upstream datasets and models by adding variables, improving data quality, and supporting multiple time frequencies.

Contribute to the automation of FP&L processes, forecasting workflows, and cost estimation models.

Build internal analytical tools and applications to support finance and business decision-making.

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-depth knowledge of business problems and translate them into quantitative and technical solutions.

Demo results and deliver concise handoff docs, runbooks, and impact metrics.

Required qualifications:

Master’s or PhD candidate or recent graduate in Data Science, Machine Learning, Computer Science, Applied Math, Statistics, Operations Research, Engineering, Finance, Economics or similar quantitative fields.

Demonstrable experience building AI prototypes or agentic projects, or quantitative/data-driven models (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 working with financial or economic data, time series, or forecasting problems.

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.

Pay: $25.00 - $30.00 per hour

Application Question(s):

• This position is fully on-site. Will you able to reliably commute to the Dallas office Monday - Thursday for this role?

Education:

• Bachelor's (Required)

Work Location: In person