Senior Data Scientist — Airline Revenue & Forecasting

Sabre; United States; Hybrid; USD 130,000 - 190,000; Full time

Benefits offered by this job

Competitive pay bonuses

Flexible work options

Healthcare coverage

Generous PTO

Strong retirement plan

Family-friendly benefits

Professional development

Reasonable Accommodation

Job summary

Sabre is seeking a Data Science Engineer to join the global Operations Research team, applying advanced statistics and ML to optimize revenue, retailing and traveler experience. You will translate complex questions into models, define KPIs, and communicate results to decision-makers.

Work involves sourcing data, building scripts in multiple languages, and collaborating with software teams to deliver production-grade forecasting and analytics solutions. Hybrid work model with global impact.

Qualifications

• Advanced degree in statistics, OR, CS, math or ML.
• Strong programming in Python and C++, plus R, SQL, PySpark, Perl, bash, Java or JavaScript.
• Experience deploying models in cloud environments (SageMaker, Forecast).
• Proven ability to translate business questions into predictive models and KPIs.

Responsibilities

• Turn operational and consumer data into actionable predictions.
• Develop, test, and calibrate data models and ML algorithms.
• Source data across diverse platforms and write data manipulation scripts in Python, R, and SQL.
• Collaborate with software engineers to productionize forecasting and analytics tools.
• Establish monitoring to evaluate data accuracy and model performance.

Skills

Python

C++

R

SQL

PySpark

Perl

Bash

Java

JavaScript

Machine Learning

Statistics

Education

Advanced degree in Statistics

Operations Research

Computer Science

Mathematics

Machine Learning

Tools

Amazon SageMaker

Amazon Forecast

Job description

Sabre is seeking a Data Science Engineer to join the global Operations Research team, applying advanced statistics and ML to optimize revenue, retailing and traveler experience. You will translate complex questions into models, define KPIs, and communicate results to decision-makers.

Work involves sourcing data, building scripts in multiple languages, and collaborating with software teams to deliver production-grade forecasting and analytics solutions. Hybrid work model with global impact.