Senior Data Scientist
- Monterrey
- Montevideo
- Remote.AR
- Remote.Colombia
- Rosario
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Client
Project overview
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.
Position overview
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.
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
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