Principal Data Science Engineer
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Job Description
Data Science Engineer leveraging statistical analysis to optimize revenue performance in airline industry. Collaborating with experts to deliver actionable predictions and insights using data models.
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.
Requirements:
- 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++.
- Experience with deployment of machine learning and statistical models on a cloud: MLOps experience within the enterprise CI/CD process to implement Sabre CI/CD for ML models
- Experience deploying ML APIs in production environments in GCP using GKE Kubernetes Service
- Experience in using GCP Vertex AI for ML and BigQuery for Datawarehouse
- Knowledge in Terraform and Containers technologies
- Experience writing data processing jobs using GCP Dataflow and Dataproc
- Experience setting up ML model monitoring and autoscaling for ML prediction jobs
- Understanding of machine learning concepts to scale ML across different services by leveraging Feature Store, Artifacts Registry.
Benefits:
- Flexible work arrangements
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