Position Description For Data Scientist, Ancillaries
Sabre Ancillaries Delivery members are part of a techno-functional team specialized in implementing and delivering Ancillary Optimization, Offer Optimization, and Dynamic Pricing solutions for airlines. The Data Scientist is recognized as a subject matter expert in data science, experimentation, model performance, and airline commercial business practices, helping customers adopt and optimize Ancillaries solutions.
Responsibilities
- Lead end-to-end data science projects, from problem definition to deployment and monitoring
- Oversee the complete solution implementation lifecycle, including project kickoff, business process assessment, and transition to customer care.
- Gain comprehensive knowledge of user interfaces to train analysts and support integration with airline business processes.
- Understand dynamic pricing and offer optimization models, collaborating with operations research teams for improved delivery to airlines.
- Design and deploy machine learning and optimization models to enhance performance and customer outcomes.
- Collaborate across all stages of implementation, from discovery to validation and customer care.
- Develop and refine predictive and statistical models for complex business challenges.
- Convert business needs into analytical frameworks, KPIs, and measurable results.
- Analyse large datasets and build reliable pipelines.
- Work with engineering and product teams to integrate models into production systems.
- Clearly communicate insights and recommendations to technical and non-technical audiences.
- Guide junior data scientists and promote best practices and innovation.
Required Experience / Skills
- Experience in data science, machine learning, optimization, or analytics roles, preferably within airline retailing, ancillaries, pricing, or revenue management.
- Good understanding of airline ancillary products, offer management, and commercial optimization concepts is preferred.
- Experience building, evaluating, and operationalizing machine learning or optimization models using large and complex datasets.
- Strong analytical and problem-solving skills with the ability to convert business questions into data-driven solutions.
- Demonstrated ability to apply statistical, modelling, and analytical techniques to solve real-world travel or commercial business problems.
- Experience with experimentation, A/B testing, feature engineering, model monitoring, and performance measurement.
- Experience interpreting model outputs and translating findings into business recommendations for stakeholders.
- Knowledge of machine learning, forecasting, optimization, or pricing models.
- Good SQL skills and experience working with relational and non-relational databases.
- Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field desired.
- Must be highly organized, able to manage multiple priorities, and comfortable working in a fast-paced environment.
- Prior experience with airline forecasting, optimization, personalization, or retailing use cases is an advantage.
- Proficient English written and verbal communication skills; ability to explain technical concepts to non-technical audiences.
- Ability to identify issues, assess business impact, and determine when escalation is needed.
- Willingness to travel as needed to support customer engagements and business priorities.
Preferred Technical Skills
- Microsoft tools: Excel, PowerPoint, Word, and data visualization tools for analysis and presentation.
- Tools: Python, R, SQL Developer, Jupyter notebooks, and analytics or experimentation platforms.
- Databases and platforms: Google BigQuery, MongoDB, and other cloud-based analytics environments.
- Operating systems: UNIX, Linux, and Windows.
- Experience with version control, scripting, and programming languages such as Python, Java, or C++ is a plus.
