Join Delta Air Lines as a Reservations Intern and help shape the future of customer care. You’ll work on high-impact projects that improve the servicing experiences for millions of customers while gaining hands-on experience in data analytics, process improvement, product management, statistical modeling, and natural language processing (NLP).

While interning in Reservations you’ll gain:

Real-world experience in a Fortune 100 company

Experience presenting to an executive audience

Mentorship and networking opportunities

Reservations serves as the point of contact for customers before, during, and after travel. This internship is a back-office role at our General Offices (GO), supporting Customer Engagement Centers by improving both customer and agent experiences.

The Reservations Intern serves as an internal consultant, leading semester-long projects that support divisional strategies and goals. These initiatives involve cross-functional collaboration to identify opportunities and recommend solutions. Projects may include analyzing customer interaction data such as call transcripts, chat logs, and survey responses using NLP techniques to improve customer experience and operational efficiency.

An ideal candidate will have educational experience in machine learning, statistical analysis, natural language processing (NLP), and data storytelling. The candidate should have strong organizational and communication skills and be comfortable in a fast-paced environment.

Partner with data scientists to develop advanced analytics solutions, including NLP use cases such as sentiment analysis, intent classification, and conversational data modeling

Collect data via SQL/Python queries and perform exploratory data analysis

Present analysis to business partners in a clear and compelling way

Currently pursuing a Master’s or Ph. D degree

Not enrolled in classes during the internship

Able to work 16 consecutive weeks

Willing to travel as required

Able to work on-site in Atlanta 2–3 times weekly

Strong team player with attention to detail

Proficient in SQL, Python, machine learning, pandas, scikit-learn, Git

Experience in corporate environments

Strong written and verbal communication skills

Experience with structured and unstructured data

Knowledge of data visualization tools (Power BI, Tableau)

Experience with NLP techniques (tokenization, embeddings, sentiment analysis, topic modeling)

Familiarity with NLP libraries such as NLTK, spaCy, or Hugging Face

Experience working with conversational or text datasets

Exposure to large language models (LLMs) and prompt engineering