Analyst - Data Scientist Machine Learning
United AirlinesMatch Score
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Protocol Intelligence
Data-driven signals on your job's competitivenessGlobal brand plus a generalist ML role at early-mid level increases qualified applicant density.
Core ML, Python, and MLOps skills transfer easily across industries despite airline domain context.
Explicit 2+ years requirement plus mandatory ML, Python, SQL, and production deployment skills increases filtering strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Lead the development and deployment of AI/ML solutions to solve complex business problems across United Airlines' departments.
Partner with business and technology teams to identify improvement opportunities, build end-to-end project pipelines, and deliver scalable machine learning models that drive revenue, engagement, and automation.
Mentor junior data scientists and contribute to research and knowledge sharing on advanced machine learning techniques, including Generative AI and foundation models.
Minimum Requirements
Bachelor's degree in Engineering, Technology, Computer Science, Statistics, Operations Research, Applied Mathematics, or Economics.
At least 2 years of full-time relevant experience in analytics/data science involving machine learning and data modeling.
Proficiency in Python and SQL with experience handling large, complex datasets, and knowledge of end-to-end machine learning lifecycle.
Experience with classification, regression, ensemble methods, gradient boosting, clustering, and building AI solutions using Generative AI and foundation models (prompt engineering, embeddings, vector search, RAG, AI agents).
Ideal Candidate Profile
Experienced data scientist with strong cross-functional collaboration skills, capable of translating business problems into effective AI/ML solutions with measurable impact.
Familiarity with advanced AI domains such as Generative AI, Large Language Models, and deploying production-grade AI/ML systems using cloud-based platforms like AWS.
Keeps current on latest machine learning models and practices, comfortable mentoring team members and working in a highly innovative and data-driven environment.