Senior Data Scientist

Leega

. Transform demand, occupancy, and purchasing behavior data into pricing models for thousands of origin-destination pairs and multi-leg routes .

Posted 9/24/2026full-timeRemote • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in statistical analysis, machine learning, and pricing model development, with a strong focus on demand modeling and causal inference. Proficient in Python and SQL, with experience in A/B testing and data visualization to drive revenue optimization.

Highest-signal resume keywords

Statistical AnalysisMachine LearningPython ProficiencyA/B TestingCausal Inference

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical AnalysisTime-Series AnalysisExploratory Data AnalysisRegressionClassificationClusteringDeep LearningElasticity ModelingLinear ProgrammingRevenue Management

Soft Skills

Clear Scientific CommunicationStorytelling

Tools & Technologies

PythonSQLPyTorchTensorFlowPandasScikit-learnStatsmodelsXGBoostLightGBMSHAP

Certifications & Qualifications

Graduate Degree (Master’s or PhD)

Industry Keywords

Pricing ModelsDemand ModelingCausal InferenceA/B TestingRevenue Optimization

Tech Stack

Tools & technologies

JavaScriptPandasPythonPyTorchRayScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Transform demand, occupancy, and purchasing behavior data into pricing models for thousands of origin-destination pairs and multi-leg routes
Conduct exploratory and statistical analyses to uncover patterns, develop hypotheses, and guide modeling efforts
Model demand and no-shows using gradient boosting and time-series methods, correcting for censored-demand bias
Estimate price elasticity and willingness to pay by segment and route
Model seat protection and capacity allocation on multi-leg routes, balancing occupancy and revenue
Design A/B tests and apply causal inference to validate pricing changes and measure uplift
Ensure model interpretability, including the use of SHAP, to justify pricing decisions to the business and regulators
Develop cold-start and calibration strategies for routes with limited historical data
Collaborate with ML engineers, data engineers, and commercial and operations teams
Formulate hypotheses, validate them with statistical rigor, and influence revenue and margin across millions of trips per year

Requirements

What you’ll need

Strong quantitative background in Statistics, Economics, Mathematics, Engineering, Computer Science, or a related field
Solid foundation in probability, inference, and experimental design
Experience with exploratory data analysis (EDA), storytelling, and visualization
Knowledge of classical machine learning, including regression, classification, and clustering
Knowledge of time-series analysis
Familiarity with deep learning using PyTorch or TensorFlow
Proficiency in Python and the Data Science ecosystem, including pandas, scikit-learn, and statsmodels
SQL for large-scale data
Causal inference and/or A/B testing and impact measurement
Clear scientific communication
Comfortable with AI-assisted development using Claude Code
Knowledge of XGBoost, LightGBM, EconML, DoWhy, MLflow, Ray Tune, SHAP, Cube.js, and Athena
Experience or knowledge in elasticity, fare buckets/seat protection, linear programming, and revenue management is a plus
Graduate degree (Master’s or PhD) and experience with LLMs/RAG are a plus

Benefits

Comp & perks

Ongoing professional development
Potential project extension or permanent employment after the six-month project
Remote work