Senior Data Scientist

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Leega

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2010

🔌 API

🤖 Artificial Intelligence

API • Artificial Intelligence • Cloud Solutions

Leega is a leading technology solutions provider in Latin America, specializing in data analytics and cloud solutions. As the first company in the region certified by Google Cloud for Data Analytics, Leega offers a range of services including application development, machine learning, and risk management analytics. The firm partners with major cloud services such as AWS and Microsoft Azure to help businesses enhance their data management and transition effectively to the cloud, ultimately driving digital transformation and innovation.

📋 Description

• You will transform demand, occupancy, and purchasing behavior data into models that price a network with thousands of origin-destination pairs and multi-leg routes. • Conduct exploratory and statistical analysis to discover patterns, generate hypotheses, and guide modeling. • Model demand and no-shows per origin-destination pair using gradient boosting and time series methods, correcting for censored demand bias (unconstrained demand). • Estimate price elasticity and willingness-to-pay by segment and route as the basis for price optimization. • Model seat protection and capacity allocation (fare buckets) on multi-leg routes, balancing load factor and revenue. • Design A/B tests and causal inference analyses that validate price changes and measure real uplift, with clear statistical rollout criteria. • Ensure interpretability (e.g., SHAP) to defend each price to the business and regulators. • Design strategies for routes with limited historical data, starting from literature priors and evolving to ML solutions, on a per-tenant basis.

🎯 Requirements

• Strong quantitative background (Statistics, Economics, Mathematics, Engineering, Computer Science or related) and a solid foundation in probability, inference, and experimental design. • Exploratory data analysis (EDA) and strong storytelling and visualization skills. • Classical ML (regression, classification, clustering) and time series; familiarity with deep learning (PyTorch or TensorFlow). • Python and the Data Science ecosystem (pandas, scikit-learn, statsmodels); SQL for large-scale data. • Causal inference and/or A/B testing and impact measurement. • Clear scientific communication and comfort with AI-assisted development (e.g., Claude Code).

🏖️ Benefits

• Remote work • Project duration: 6 months, with possibility of extension or internal hire.