Ph.D Intern - Optimization (Spring 2027)

Delta Air Lines, Inc.; Atlanta (GA); On-site; USD 30,000 - 41,000; Full time

Job summary

Delta Air Lines, Inc. is seeking a graduate operations research intern to develop data-driven solutions that support decision-making and improve airline efficiency and performance.

The role requires knowledge of optimization models, simulation, and data science concepts, with emphasis on communication skills and a fast-paced environment. It will contribute to decision support applications using combinatorics, algorithms, and optimization.

Qualifications

• Pursuing BA/BS in IE, Stats, Math, CS or related field.
• PhD coursework completed (minimum one year).
• Strong quantitative problem-solving ability.
• Knowledge of optimization techniques (LP/MILP/CP/heuristics).
• Proficient in Python; C++ or similar.
• Excellent written and verbal communication.
• Authorized to work in the United States.

Responsibilities

• Build complex data sets from multiple data sources.
• Develop and calibrate optimization products.
• Deliver decision support applications.
• Interface with business unit leaders to align on needs.
• Practice safety-conscious data handling and governance.

Skills

Python

C++

Optimization

SQL

Machine Learning

AWS

Communication

Teamwork

Safety awareness

Education

BA/BS in Industrial Engineering, Statistics, Mathematics, or Computer Science

PhD coursework (minimum one year)

Tools

Gurobi

Cplex

GLPK

SQL

Relational databases

Python

AWS

Job description

How You'll Help Us Keep Climbing (Overview & Key Responsibilities)

The Operations Decision Science team at Delta Air Lines is seeking a graduate operations research intern to develop data-driven solutions aimed at continually providing decision support while improving airline efficiency and performance.

An ideal candidate has foundational technical knowledge of operations research optimization models, simulation models, and core data science/data engineering concepts. The candidate should have excellent organizational and communication skills and feel comfortable in a fast-paced environment. This role will support the delivery of decision support applications by leveraging combinatorics, algorithms, and optimization.

Primary Functions

• Build complex data sets from multiple data sources, both internally and externally
• Leverage emerging technologies and identify efficient and meaningful ways to disseminate and synthesize data to satisfy business’ needs
• Design, develop, implement, and calibrate optimization products
• Interface with business unit leaders to develop and maintain internal customer relationships
• Practice safety-conscious environment resulting in employee safety and well-being

What You Need To Succeed (Minimum Qualifications)

• Working as an intern does not guarantee a full-time opportunity upon graduation. This position is intended to provide you with educational, and professional work experience to prepare you for the workforce.
• This position requires you to work from January 2027 - May 2027. You cannot actively take any courses (inclusive of online or in-person) and work as an intern at the same time.
• BA/BS in Industrial Engineering, Statistics, Mathematics, Computer Science, or related field
• Minimum of one year of doctorate level coursework completed PhD
• Proven success in solving complex quantitative problems
• Working knowledge in one or more optimization techniques (LP, MILP, QCP, MIQP, CP, and/or heuristics)
• Proficiency in Python, C++ or other programming languages (Python preferred)
• Strong written, oral communication, and interpersonal skills
• 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)

• Working knowledge in commercial optimization solvers (Gurobi, Cplex, GLPK, etc.)
• Working knowledge in model tuning/calibration
• Proficiency in working with relational databases and query authoring (SQL)
• Fundamental Machine Learning techniques, including reinforcement learning
• Working knowledge of AWS