Applied Scientist with Causal Inference

About the Position

We are looking for an Applied Scientist to lead the methodological strategy for experimentation and causal inference in a cargo analytics environment. You will design rigorous analytical approaches, analyze impact, and help integrate causal methodologies into business and product decision making.

About the Project

Cargo Analytics Platform is focused on building robust analytical capabilities at scale through experimentation, causal inference, and data products. The team applies rigorous scientific methods to complex cargo challenges using Python, SQL, BigQuery, and statistical tooling.

About the Team

You will work with a cross functional team that includes Data Scientists, Tech References, Engineering, Product, and business stakeholders. The collaboration style is hands on and closely aligned around embedding analytical methods into data products and decision processes.

Responsibilities

• Lead the methodological strategy for experimentation and causal inference
• Design and analyze experiments, A B tests, quasi experiments, and observational studies
• Develop and apply causal inference methods to measure impact and support decisions under uncertainty
• Translate business questions into robust analytical designs
• Build capabilities for value capture measurement, incremental impact, and systematic learning
• Collaborate with Data Scientists, Engineering, Product, and business stakeholders to integrate causal methodologies into data products and decision processes
• Contribute to the evolution of standards, tools, and best practices for experimentation

Requirements

• Solid experience as an Applied Scientist, Data Scientist, or in a similar quantitative role with demonstrable depth in experimentation and causal inference
• Strong foundations in statistics, statistical inference, and experimental design including A B testing, quasi experiments, and observational studies
• Proficiency in Python for statistical analysis and modeling using Statsmodels, Scikit learn, and Pyfixest or a similar framework for causal or panel estimation
• Proficiency in SQL and experience with BigQuery or an equivalent cloud data warehouse
• Ability to frame business problems analytically and translate them into rigorous designs
• Experience measuring impact, incrementality, and value capture
• Strong data storytelling and the ability to communicate findings to technical and non technical stakeholders
• Fluency in Spanish and intermediate English for documentation and international collaboration

Nice to Have

• Predictive modeling and machine learning fundamentals applied to decision making
• Familiarity with responsible AI and analytical ethics practices

Technologies

Python, SQL, BigQuery, Statsmodels, Pyfixest, Scikit learn