Analyst - Data Scientist Machine Learning
United Airlines
Come join us to create what’s next. Let’s define tomorrow, together.
Description
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
· 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 Operations-Research-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, reduce costs, and boost customer engagement by leveraging state-of-the-art Operations Research (OR) techniques
· Data Scientists contribute in developing smart and innovative solutions across many of United’s departments
· Working on projects in partnership with business teams to identify opportunities for improvement and gathering and analyzing information and data
· Delivering high quality OR solutions and maintaining proper documentation to foster seamless workflows and code-reusability principles
· Effectively structuring communication of insights from workstreams and delivering clear and professional presentations to the team/team leaders/managers/stakeholders
· Performing regular technical coordination/reviews with stakeholders and ensuring timely reporting and escalations if any
· This position is offered on local terms and conditions. Expatriate assignments and sponsorship for employment visas, even on a time-limited visa status, will not be awarded.
Qualifications
What you’ll need to succeed (Minimum Qualifications)
- Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Computer Science, or Operations Research
- 2+ years of hands-on experience in machine learning, statistical modeling, or applied data science
- Strong curiosity and comfort working with large, complex datasets, with experience in predictive modeling
- Proficiency in Python, with experience using modern ML libraries (e.g., scikit-learn, TensorFlow, PyTorch)
- Experience analyzing high-volume, high-dimensional data from multiple sources to uncover patterns and insights
- Solid understanding of machine learning techniques such as logistic regression, random forest, gradient boosting, neural networks, and SVMs
- Foundational knowledge of deep learning concepts and architectures (e.g., CNNs, RNNs, transformers)
- Familiarity with emerging areas such as Generative AI (e.g., LLMs, prompt engineering, embeddings) and/or computer vision is a plus
- Proficiency in SQL, with experience writing complex queries and working with relational databases
- Familiarity with cloud platforms, preferably AWS (e.g., S3, EC2, SageMaker, Lambda), for data processing and model development
- Ability to clearly communicate complex analyses and translate them into actionable insights
- Legally authorized to work in India without sponsorship
- Fluent in English (written and spoken)
- Successfully complete the interview process and meet role requirements
What will help you propel from the pack (Preferred Qualifications):
- Master’s degree in a relevant field
- Hands-on experience with deep learning, computer vision, or NLP applications
- Experience working with Generative AI use cases (e.g., LLM-powered applications, retrieval-augmented generation, prompt design)
- Experience building and deploying ML models on AWS (e.g., SageMaker pipelines, model deployment, monitoring)