Position Overview
Stantec is seeking a motivated Data Analytics and AI Innovation Intern to join our Lexington, KY team for Summer 2026, typically May–August, full-time. This internship offers a unique opportunity to apply cutting-edge AI, data analytics, and innovation skills to real-world engineering workflows in water resources, environmental services, and infrastructure projects. You will work closely with project teams, including experienced engineers and collaborating researchers to evaluate AI tools, develop practical standard operating procedures (SOPs), and contribute directly to technical tool development. This role provides hands-on experience bridging AI innovation with practical engineering applications.
Key Responsibilities
- Evaluate and recommend AI-powered tools and technologies tailored to Stantec's engineering workflows, with a focus on improving efficiency and quality in daily tasks.
- Develop practical SOPs and implementation guides for AI-assisted engineering activities, such as generating high-quality meeting minutes, presentation summaries, or action items, automating the creation or drafting of professional engineering reports and documents, and implementing automated quality review and consistency checks for reports, calculations, spreadsheets, and deliverables.
- Actively contribute to 1–2 ongoing technical tool development efforts, with hands-on coding and problem-solving, utilizing a combination of coding, modeling, and analytical skills.
- Collaborate with multidisciplinary teams to test, document, and refine AI-driven solutions.
- Participate in team meetings, project reviews, and professional development sessions as part of Stantec’s internship program.
Qualifications
- Current college junior or senior pursuing a bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering (with strong computational focus), or a closely related discipline.
- Strong programming skills in Python (preferred) or Java; experience with libraries such as pandas, numpy, scipy, or similar for data processing and simulation.
- Familiarity with AI/ML concepts and tools (e.g., large language models, prompt engineering, or basic generative AI applications) is highly desirable.
- Coursework in probability and statistics strongly preferred; familiarity with statistical modeling, uncertainty quantification, or Monte Carlo methods is a plus
- Interest in applying technology to engineering/environmental challenges (experience in civil/environmental engineering or water resources is a plus but not required).
- Excellent analytical, problem-solving, and communication skills.
How to Apply
Interested candidates should submit a resume and unofficial transcript.
