Analyst - Data Scientist Machine Learning

United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions.

Job overview and responsibilities

High-level statement outlining the overall objective or reason the job exists. Should be 3 to 5 sentences. This should not read like a job posting (i.e. do not use the word “candidate”).
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 in developing smart and innovative solutions across many of United’s departments.

• Working on projects in conjunction with business teams to identify opportunities for improvement, gather and analyze information and data, develop improvements and innovations
• Apply knowledge of statistics, machine learning, programming, and data modeling to recognize patterns, identify opportunities, evaluate business opportunities, and deliver valuable insights
• Effectively structure communication of insights from work streams and deliver clear and professional presentations to the team/team leaders/managers/stakeholders
• Apply techniques including regression models, decision trees, random forests, gradient boosting, support vector machines, clustering, and NLP/CV algorithms
• Formulate and develop end-to-end project pipelines to deploy scalable solutions on company platforms
• Execute solutions to business problems using data analysis, machine learning and optimization tools
• Research latest machine learning approaches and share the knowledge across the team