The Analytics and Innovation (Ai) team at United Airlines works to innovate, transform, and solve complex business problems resulting in significant and measurable enterprise impact through the application of deep cross-functional business expertise and advanced analytics. We work with business and technology partners across the enterprise (e.g. Airport Operations, Contact Centers, Network Planning, Revenue Management, Digital Products, Human Resources, etc.) to influence strategic decisions, enterprise strategy, business process, and to help connect the dots across the enterprise. We aim to be an organization with whom and within everyone loves to work!
Data Scientists within Ai partner with business and technology leaders across the company to deploy AI & ML powered solutions to support and automate business processes. The team works closely with other teams in digital technology with complementing skills and capabilities. The key objectives are to drive incremental revenue, boost customer engagement and to automate manual processes by leveraging state-of-the-art ML techniques. Data Scientists contribute to developing smart and innovative solutions across many of United’s departments. Data Scientists contribute to developing smart and innovative solutions across many of United’s departments. A growing share of this work involves Generative AI and agentic systems — LLM-powered assistants, and multi-modal AI (Voice and Image)— deployed into production to augment contact center, operations, and customer-facing teams. Data Scientists are expected to grow comfortable working alongside these techniques in addition to classical machine learning.
Job overview and responsibilities
Work with other data scientists and a variety of stakeholders (IT, DE, business, etc.) to gather and analyze data on United's various operations, delivering high-quality models and fact-based, data-driven recommendations
Execute solutions to business problems using data analysis, machine learning and optimization tools, GenAI/LLM techniques (e.g., Agentic, prompt engineering), and optimization tools
Execute and deploy solutions by leveraging the latest AI-assisted tools and techniques — such as coding agents, AI design and prototyping tools, and agentic frameworks — to rapidly prototype, build, and ship high-quality solutions with greater speed and efficiency
Work with multiple multi-modal models spanning text, voice, and vision, and build data transfer pipelines and model monitoring to support their scalable deployment
Research latest ML, DL and GenAI approaches to enable solutions to solve for different vertical teams and also to share the knowledge across the team
Effectively structure communication of insights from work streams and deliver clear and professional presentations to the team/team leaders/managers
Partner and engage with data engineering and operations teams to inform and support business stakeholders with day-to-day project updates.
Required Qualifications:
BTech/Bachelor’s degree
Engineering, Technology, Computer Science, Statistics, Operations Research, Applied Mathematics, Economics
Full time or internship experience in analytics/data science
0-3 years relevant work experience
Excellent analytical and problem-solving skills
Proficiency in Programming Languages (Python/R), SQL, Excel and other Microsoft Office products
Intermediate knowledge in machine learning algorithms like Bagging (Decision Trees, RF), Boosting (XGBoost, GBM) , Clustering (KMeans)
Proven comfort and an intellectual curiosity for working with very large sets of data
Understanding of probability & statistics
Ability to bridge business context with technical details and explain and discuss mathematical and machine learning technicalities to a business audience
Strong interpersonal skills with a focus on teamwork
Preferred Qualifications:
MTech/Master’s degree
Data Science, Business Analytics, Engineering, Technology, Computer Science, , Statistics, Operations Research, Applied Mathematics, Economics
Knowledge of deep learning/neural networks and experience with NLP/CV
Exposure to Large Language Models (LLMs), and Agentic application design and frameworks (e.g. Langgraph/Langchain)
Hands-on ability to use modern AI tools (e.g., LLMs and AI-assisted development tools) to prototype and build products and solutions
Hands on experience in using AWS/Azure etc