Data Scientist
Core
Design causal-uplift measurement frameworks and translate complex multidimensional data into actionable insights for airline pricing algorithms.
Role type
Senior data scientist (causal inference & uplift modeling)
Builds
Causal-uplift measurement frameworks and pricing algorithm insights
Domain
Aviation / Transportation / Logistics
Deliverable
dashboards & analysis
Required skills
Python (pandas, numpy, scikit-learn, statsmodels), SQL (BigQuery, Dataform, GCP), causal inference, uplift modeling, A/B testing, statistical analysis, mathematical optimization
Preferred skills
Domain knowledge in airlines/transportation/logistics, anomaly detection, mathematical optimization
Responsibilities
Design and operationalize causal-uplift measurement frameworks to quantify incremental impact of pricing models; Lead data discovery and translate complex multidimensional data into actionable insights related to pricing algorithms; Conduct research and experimentation to elaborate novel approaches to uplift measuring and A/B testing; Collaborate with revenue managers, data analysts, and data engineers to encode airline business logic into modeling and technical pipelines
Seniority
Senior, hands-on IC
