Delta Air Lines, Inc. PROJECT LEADER-OAP in Atlanta, Georgia
The Analytics Leader will be responsible for analyzing and developing Delta Pulse CX insights based on survey data. In partnership with operating divisions, the analytics leader will help identify customer experience pain points and develop a road map to mitigate and resolve challenges. In addition, the analytics leader will lead cross-divisional corporate operational initiatives to develop enterprise level solutions. The Analytics leader brokers and manages tradeoff discussions between various divisional leaders to develop comprehensive solutions. The analytics leader will also support C suite executive reporting. Demonstrates self-starter initiative, is accountable for accuracy of highly visible content, manage priorities and asserts quality decision making in order to meet deliverable requirements.
Bachelor's degree and at least 5 years of related experience (strongly prefer MBA, Computer Science, Statistics, and/or Data Science) OR MS degree in a quantitative discipline with at least 3 years of related work experience is required.
Must have superior technical, quantitative/analytical, organizational skills and demonstrate critical thinking with respect to cause & effect relationships.
Data analysis and mining experience required and must be able to quickly learn new data subject areas. Must have ability to anticipate and plan for competing priorities, and negotiate deliverables accordingly.
Project management experience with large-scale, cross-functional projects required and must be able to successfully execute and manage the scope, schedule and budget of multiple projects.
Must be able to work in a fast paced team environment with minimal supervision.
Must be comfortable working in group and individual settings and frequently presenting to leaders.
Must be performing satisfactorily in current position.
Successful candidates will have the following proficiencies
Working with relational databases and query authoring (SQL)
Data Model building (Python, R, SAS, and other machine learning and analytical platforms)
Statistical analysis and modeling including Linear Regression, Segmentation, non-linear predictive (e.g. Logistic) regression.