United Airlines Data Scientist in Chicago, Illinois
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Technical Operations includes the maintenance, and overhaul of our aircraft. This includes aircraft maintenance technicians, engineers, planners, ground equipment and facilities teams, supply chain teams and more.
Job overview and responsibilities
The Data Scientist will collaborate with the Analytics Products team and business SMEs to deliver machine learning solutions and provide consulation on machine learning techniques and technology. Our Analytics Products group is a global team energetic about using data to develop products or data-driven strategic solutions across United Airlines. We partner with subject matter experts across the business to build solutions for a wide variety of commercial and operations use cases. As a team, we focus on projects that drive strong financials, deliver improved customer experiences and support employee engagement. The data science team within Analytics Products focuses on predictive modeling, particularly with complex data, such as unstructured image and text, signal and time series data.
Synthetize and analyze data to be incorporated in the spare parts forecasting systems.
Support strategic Supply Chain initiatives with analysis accompanied by actionable recommendations.
Ensure alignment and prioritization with business objectives and initiatives – helping business owners make faster and smarter decisions.
Maintain, enhance and otherwise support a portfolio of existing analytic tools and ensure they continue to stay valuable and relevant.
Collaborate with stakeholders (both frontline and executive-level) to identify processes strategies, or decisions that can be improved by leveraging analytic insight.
Develop and validate performance metrics and models to identify operational and financial improvement opportunities.
Individually develop and execute toward project plans.
Bachelor's degree in a quantitative field such as math, statistics, operations research or engineering required
Specialization in Data Analytics, i.e. Machine Learning, Databases management, applied statistics
Two to five years of experience in an analytics or process improvement-oriented role required
Baseline understanding of supply chain functions including sourcing/procurement, vendor management, inventory planning, warehousing, and logistics
Familiarity with database models, i.e. RDBMS, Hadoop, with high-level proficiency integrating and otherwise manipulating complex transactional data in relational databases using SQL
Familiarity with scripting programming languages, i.e. R, SAS, Python
Familiarity with Machine Learning techniques
Familiarity with data visualization tools, i.e. TIBCO Spotfire, Tableau, MS-Power BI or equivalent
Must be legally authorized to work in the United States for any employer without sponsorship
Successful completion of interview required to meet job qualification
Reliable, punctual attendance is an essential function of the position
Master's degree in a quantitative field such as math, statistics, data science/machine learning, operations research, engineering and/or MBA preferred
Six Sigma Black Belt certification preferred
Project management experience preferred
Experience in operations research, industrial engineering or related field involving solving complex business problems preferred
Experience developing and deploying machine learning models on platforms such as AWS, Azure, Sales Force or Google Cloud platforms
Familiarity with maintenance, repair, and overhaul (MRO) functions
Familiarity with the airline industry
Strong background in one or more supply chain functions
Experience with machine learning techniques, i.e. Natural Language Processing, Computer Vision
Familiarity with Deep Learning techniques
Familiarity with ERP systems
Familiarity with Multi-Echelon Supply Chain models
Familiarity with Spare Parts Inventory Planning methods, i.e. METRIC
Applied understanding of process improvement methodologies such as lean and six sigma.
At least one years of airline experience preferred
At least one year of supply chain experience preferred
Equal Opportunity Employer – Minorities/Women/Veterans/Disabled/LGBT
Division: 66 Technical Operations/Maintenance
Function: Tech Ops / Maintenance - Management & Administrative
Equal Opportunity Employer – Minorities/Women/Veterans/Disabled