Principal Data Scientist

Company

Alaska Airlines

The Team

Guided by our purpose, core values, and leadership principles, we are creating an airline people love. Our corporate teams set the strategies and operational plans to ensure the success of our company. Whether we use our expertise in accounting, human resources, finance, planning, legal, marketing, or any of our operational divisions, our shared passion for travel and our guests is what motivates us to achieve excellence each day. If you share our passion for creating an airline people love, we want to hear from you. 

Role Summary

As a member of the Enterprise Data Science Team, the Principal Data Scientist is a subject matter expert in translating business strategy into advanced analytical models and experiments to optimize Alaska Airlines’ performance across system operations, flight operations, inflight, maintenance and engineering, airport operations, scheduling, network planning, marketing, and revenue management. As an individual contributor this role defines the long-term strategy around statistical modeling and research, optimization, development and delivery of ML/AI models, project management, and solution design/delivery.

Key Duties

• Acts as a data and business information subject matter expert in the development of requirements and solutions for leadership, strategy, and operational data.
• Translates strategy into advanced analytical experiments to align performance with the company's strategic goals.
• Develops and deploys machine learning models to drive business decisions and create value for Alaska Airlines. Creates detailed action plans, key performance indicators, and progress metrics.
• Exercises considerable latitude and initiative to solve for continuous improvement processes through data-driven analysis, reporting, tools, and goal setting to drive incremental improvement for key areas.
• Advocates for and understands the full data lifecycle, including data collection, data mining, data integration, data analysis, extracting insights, and results visualization.
• Investigates and combines new and disparate large-scale data sources to extend the data-driven business process.
• Develops and implements systems and technology to produce decision support tools that enable leaders and system practitioners to take strategic action in a dynamic, competitive environment.
• Develops, maintains, and owns performance of automated systems to perform strategic activities. Researches new data sources and analytical tools to enhance the data-driven business process.
• Influences and networks across stakeholders and ITS on the integration and support of business systems.
• Mentors and supports the development of other analysts throughout the company, acting as a leader for the Operations Analytics Team and an ambassador to other analyst teams.
• Closely partners with Product Management teams in ITS and Ecommerce to align on development and deployment of AI/ML modeling into application roadmaps supported through those teams.
• Provide subject matter expertise in the understanding and application of Alaska Airlines and Horizon Air’s data.
• Oversees advanced research and analytic projects and presents findings and recommendations to senior leadership.
• Incorporates AGILE and software development methods with ITS and Ecommerce business units to deploy production-level data science solutions.
• Continuously monitor and enhance model performance, ensuring they meet and exceed business objectives and deliver tangible results.

Job-Specific Experience, Education & Skills

Required

• 7 years of experience in data science, operations research, or related area.
• Bachelor’s degree in a relevant field, or an additional 2 years of relevant training/experience in lieu of this degree.
• Strong experience in data mining, cleaning, manipulation, and preparation.
• Comfortable in Python, with 1+ year experience working with Pandas, Numpy, and ML toolkits such as SciKit Learn, XGBoost, PyTorch, and Tensorflow.
• Experience managing program packages and repositories to be deployed as a service.
• Advanced skills in SQL.
• Basic database design experience using databases such as Oracle, SQL Server, etc.
• Demonstrated expertise in visualization techniques; experience using data visualization tools such as Tableau, Power BI, etc.
• Experience in developing optimization/simulation models.
• Strong knowledge of descriptive and diagnostic statistics (including Bayesian stats), sampling methodology, residuals analysis / ANOVA, hypothesis / significance testing, and experimental design.
• Modeling proficiency in unsupervised and supervised machine learning, such as linear and logistic regression, KNN, cluster analysis, an