Senior Data Scientist
About the Position
We are seeking a Senior Data Scientist to analyze complex airport operational and passenger-experience problems using statistics, segmentation, ML/NLP, and experimental methods. This role requires autonomy, depth of analytical thinking, strong storytelling, and the ability to influence cross-functional teams. You will work at the intersection of analytics, product, and airport operations to generate insights that guide decisions and accelerate impact.
About the Project
The Airport Touchpoint domain covers everything a passenger experiences inside the airport—from arrival to departure—as well as all ground operations that support their journey (check-in, kiosks, counters, boarding). The goal is to deliver a seamless experience, prioritize high-value customers, and enable more efficient operational processes across airports in LATAM. This role focuses on deep problem discovery (“diamante del problema”), using statistical analysis, ML/NLP, segmentation, and exploratory analytics to uncover insights, identify improvement or value-capture opportunities, and generate strong evidence for prioritizing solutions and informing strategy.
Responsibilities
- Analyze complex business and operational problems using statistical modeling, clustering, NLP, and exploratory analytics.
- Generate actionable insights and evidence to guide strategic prioritization for airport teams.
- Apply advanced statistical methods: hypothesis testing, inference, and multivariate analysis.
- Conduct segmentation, clusterization, PCA, embeddings, and other dimensionality reduction techniques.
- Build lightweight ML and NLP models (topic modeling, classification, semantic grouping).
- Design experiments and apply causal inference frameworks.
- Develop reproducible analytical pipelines and datasets using Python + SQL.
- Create dashboards and visualizations for decision-making (executive-focused).
- Collaborate with Product, Airport Operations, Data Engineers, and cross-functional squads to guide strategy with data.
- Promote analytical rigor, documentation, reproducibility, and data-driven decision-making.
Requirements
- 5+ years of experience in Data Science, Applied Analytics, or related roles.
- Strong foundations in statistics, hypothesis testing, inference, and multivariate analysis.
- Experience with segmentation, clustering, PCA, embeddings.
- Hands-on experience in ML/NLP techniques (topic modeling, classification, semantic analysis).
- Strong background in experimental design and causal inference.
- Proficiency in Python (Pandas, NumPy, scikit-learn, StatsModels) and advanced SQL.
- Experience building end-to-end ML models and reproducible analytical pipelines.
- Strong data visualization skills and ability to create decision-oriented dashboards.
- Excellent communication and storytelling for executive audiences.
- Ability to influence without authority in cross-functional environments.
- Experience working in Agile environments.
- Fluency in Spanish.
- Good spoken English (for documentation and collaboration).
Nice to Have
- Experience in airport operations or logistics.
- Familiarity with GCP tools (BigQuery, Dataform, Dataflow, Pub/Sub).
- Experience scaling analyses and collaborating closely with Data Engineers.
- Analytical curiosity and deep problem understanding.
- Experimental and impact-oriented mindset.
- Autonomy, ownership, and critical thinking.
- Ability to turn complex findings into actionable recommendations.
- Clear communication with both technical and non-technical teams
