Data Scientist - Ops Performance

United Airlines•Chicago, IL

13h

About The Position

At United, we care about our customers. To be the best airline in aviation history, we need to deliver the best service to our customers. And it takes a whole team of dedicated customer-focused advocates to make it happen! From our Contact Center to customer analytics, insights, innovation, and everything in between, the Customer Experience team delivers outstanding service and helps us to run a more customer-centric and dependable airline. Job overview and responsibilities Collaborate with cross-functional teams like Tech Ops, NOC to design, develop, and maintain predictive models that drive actionable insights and optimize various aspects of our airline operations with an emphasis on Tech Ops performance. Engage with domain experts to understand business challenges, identify data-driven opportunities, and enhance decision-making and operational efficiency in the intersection of Tech Ops and NOC business process Conduct data mining, data cleaning, and feature engineering to ensure high-quality datasets for analysis and modeling, in order to reduce unplanned out of service aircraft or improve throughput or mitigate risk for Tech Ops operation Develop, utilize state-of-the-art models (e.g. machine learning, statistics or optimization) models and advanced analytics solutions to create actionable business insights for better future operational outcomes to enable data-driven decision making within demand, supply and buffers as it relates to Tech Ops performance Effectively communicate complex data insights and model results to non-technical stakeholders in a clear and concise manner Stay current with industry trends, emerging technologies, and best practices in data science and machine learning to ensure the continuous improvement of our analytics capabilities

Requirements

Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field
4 years of experience or schooling in data science, machine learning, optimization, statistics or a related field
1+ years designing and programming/coding data structures for large-scale computer models
Coursework or work experience with statistics, machine learning, optimization, big data analytics and/or forecasting techniques
Ability to work with cross functional groups, strong relationship building skills
Demonstrated expertise in designing, developing, and deploying machine learning models and advanced analytics solutions with business results.
Proficiency in Python or R and experience with machine learning libraries
Familiarity with SQL and experience working with relational and non-relational databases
Exceptional analytical, problem-solving, and critical thinking skills
Excellent communication and presentation skills, with the ability to convey complex concepts to non-technical stakeholders.
Strong interpersonal, verbal and presentation skills
Highly organized, and the ability to multi-task competing priorities
Demonstrated ability to create business value
Willing and able to travel up to 10%
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

Nice To Haves

Master's degree or higher is preferred
1+ years of airline business experience
Tech Ops, NOC, NP or Flight Ops experience
Black Belt certification and demonstrated results through utilization of DMAIC
Prior experience in the aviation industry or a strong understanding of airline operations is a plus
Knowledge of United/industry data sources
Structured programming for large-scale computer models

Responsibilities

Collaborate with cross-functional teams like Tech Ops, NOC to design, develop, and maintain predictive models that drive actionable insights and optimize various aspects of our airline operations with an emphasis on Tech Ops performance.
Engage with domain experts to understand business challenges, identify data-driven opportunities, and enhance decision-making and operational efficiency in the intersection of Tech Ops and NOC business process
Conduct data mining, data cleaning, and feature engineering to ensure high-quality datasets for analysis and modeling, in order to reduce unplanned out of service aircraft or improve throughput or mitigate risk for Tech Ops operation
Develop, utilize state-of-the-art models (e.g. machine learning, statistics or optimization) models and advanced analytics solutions to create actionable business insights for better future operational outcomes to enable data-driven decision making within demand, supply and buffers as it relates to Tech Ops performance
Effectively communicate complex data insights and model results to non-technical stakeholders in a clear and concise manner
Stay current with industry trends, emerging technologies, and best practices in data science and machine learning to ensure the continuous improvement of our analytics capabilities