Senior Data Scientist

Role overview

• check_circle Exploratory analytical frameworks that uncover elasticity patterns across travel datasets
• check_circle End-to-end elasticity models grounded in strong statistical methodology
• check_circle Robust evaluation frameworks to validate model assumptions
• check_circle Production-ready model architectures with data engineering
• check_circle Clear analytical insights that inform product and pricing strategy
• check_circle A clear exploratory analysis of key travel datasets identifying the most promising areas for elasticity modeling
• check_circle A defensible view of elasticity across priority datasets
• check_circle A validated modeling framework with documented assumptions and robustness checks
• check_circle A proposal for production deployment of elasticity models
• check_circle Alignment with the product roadmap
• check_circle Strong cross-functional collaboration with product, engineering, and data teams
• check_circle Exploring large-scale travel datasets to identify patterns and opportunities related to demand elasticity
• check_circle Designing and building elasticity models end-to-end
• check_circle Evaluating model robustness and statistical validity
• check_circle Translating findings into clear product and pricing insights
• check_circle Collaborating with data engineering to productionize models and pipelines
• check_circle Communicating statistical insights clearly to product and leadership stakeholders
• check_circle Databricks (core platform)
• check_circle AWS
• check_circle Large-scale data lake architecture
• check_circle High-volume travel datasets
• check_circle Has experience building elasticity or demand models in production
• check_circle Brings strong applied statistics and experimentation skillsIs comfortable working with large, complex datasets
• check_circle Can evaluate and communicate model quality clearly
• check_circle Owns projects end-to-end with high autonomy
• check_circle Works collaboratively with a low-ego mindset

Preferred qualifications

• Experience working with travel or airline datasets
• Experience proposing production architectures for data science systems
• Work on high-impact analytical problems
• Collaborate with experienced engineers and product leaders
• Take real ownership of complex systems
• Turn data discovery into product impact
• Recruiter screening
• Hiring manager interview
• Collaborative working session
• Final conversation

About the company