Graduate Intern, Reservations (Data Science) - Spring 2027

Delta Air Lines Inc

  • Atlanta, GA
  • 12 days ago

    Highlights

    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). 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.

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    LocationAtlanta, GA

    Description

    Graduate Intern, Reservations (Data Science) - Spring 2027

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    Graduate Intern, Reservations (Data Science) - Spring 2027

    United States, Georgia, Atlanta

    Reservations & Cust. Care

    27-Oct-2026

    Ref #: 34738

    How you''ll help us Keep Climbing (overview & key responsibilities)

    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

    What is Reservations?

    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.

    Job Summary

    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.

    What are we looking for?

    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

    What you need to succeed (minimum qualifications)

    • 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
    • Consistently prioritizes safety and security of self, others, and personal data.
    • Embraces diverse people, thinking, and styles.
    • Possesses a high school diploma, GED, or high school equivalency.
    • Is at least 18 years of age and has authorization to work in the United States.

    What will give you a competitive edge (preferred qualifications)

    • 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

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