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Data Scientist with Airline Revenue exp

Remote · USA Full-time New today

Data Science Engineer - Remote Responsibilities • Work with subject matter experts from airlines to identify opportunities for leveraging data to deliver insights and actionable prediction of customer behavior and operations performance. • Assess the effectiveness and accuracy of new data sources, data gathering and forecasting techniques. • Develop custom data models and algorithms to apply to data sets and run proof of concept studies. • Leverage existing Statistical and Machine Learning tools to enhance in-house algorithms. • Collaborate with software engineers to implement and test production quality code for AI/ML models. • Develop processes and tools to monitor and analyze data accuracy and models’ performance. • Demonstrate software to customers and perform value proving benchmarks. Calibrate software for customer needs and train customer for using and maintaining software. • Resolve customer complaints with software and respond to suggestions for enhancements. Required Qualifications • Advanced Degree in Statistics, Operations Research, Computer Science, Mathematics, or Machine Learning. • Proven ability to apply modeling and analytical skills to real-world problems. • Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and statistical concepts (regression, properties of distributions, statistical tests, etc.). • Solid programming skills 2-3 languages out of R, SQL, Python, TensorFlow, PySpark, Java, JavaScript or C++. • Absolutely must have: graduate school level knowledge of Revenue Management models and algorithms. • Experience (minimum 4 out of 7) with deployment of machine learning and statistical models on a cloud: • MLOps within the enterprise CI/CD process for ML models – 2 years • Experience deploying ML APIs in production environments in GCP using GKE – 2 years • Experience in using GCP Vertex AI for ML and BigQuery – 1 year • Knowledge in Terraform and Containers technologies – 2 years • Experience writing data processing jobs using GCP Dataflow and Dataproc – 2 years • Experience setting up ML model monitoring and autoscaling for ML prediction jobs – 1 year • Understanding of machine learning concepts to scale ML across different services by leveraging Feature Store, Artifacts Registry and Analytics Hub – 1 year • Desirable Qualifications • Familiarity with airline, hospitality or retailing industries and decision support systems employed there. • Experience developing customer choice models, price elasticity estimation and market potential estimation. • Understanding of airline distribution, pricing, revenue management, NDC and Offer/Order Management concepts. Apply Job!

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