About the role
American Airlines is an airline company that operates a diverse fleet of aircraft. They are seeking a Senior Data Scientist to apply machine learning and statistical techniques to address complex challenges within the Technical Operations Division, focusing on maintenance and safety of aircraft.
Responsibilities:
Collaborate with teams across the business to translate their needs or challenges into machine learning or statistical problems.
Build predictive forecasting systems to model future performance on known change.
Support the development of data products through exploratory data analysis, feature engineering, and model building.
Explore and create new datasets, identify key features, and identify new ones to be used in modeling. Datasets includes subject areas such as maintenance discrepancies, production bill of work, airline flight schedules, parts and tooling inventory, aircraft out of service, productivity, etc.
Effectively communicate complex experiments, models, and analytics outputs with partners in simple and actionable way.
Able to communicate the analysis directly with leaders at the airports and within Technical Operations group. Analysis may include flight dispatch reliability, productive aircraft scheduling, execution of routine maintenance, operational performance, etc.
Design and manage feature-based datasets in Azure for streamline ML & AI.
Other duties as assigned.
Qualification:
Master's/PhD degree or Bachelor's degree with 2+ years of equivalent practical experience in a quantitative discipline (e.g., Computer Science, Data Science, Applied Mathematics, Statistics, Operations Research, Engineering, etc.)
Experience with at least one programming language (e.g., SQL, Python, R, Java), software engineering best practices (including testing and version control), and machine learning libraries
Practical experience with data extraction, cleaning, and analysis
Deep knowledge of statistical and machine learning techniques
Demonstrated aptitude for logical analysis, problem identification, and problem solving
Ability to view data from different angles to employ feature engineering techniques to better represent models
Ability to work on a diverse team or with a diverse range of coworkers
Ability to solve complex problems and puzzles in a constrained and dynamic environment
Ability to leverage understanding of the airline business and commercial goals to drive results and innovative solutions
Ability to be adaptive to new ideas and business processes in an ever-changing marketplace
Ability to challenge self and team to develop future-oriented network strategies
Ability to communicate and collaborate, work with cross-functional groups to drive outcomes which benefit the entire airline
Excellent interpersonal and communication skills with technical and non-technical audiences
Skilled at sharing knowledge to develop the expertise of the team as a whole
