New Value Solutions (NVS), a national IT consulting firm, is seeking an experienced Data Scientist / Machine Learning Engineer based in Mexico to support a major Canadian airline on a Finance initiative focused on developing a predictive cost model. The Data Scientist / Machine Learning Engineer will work closely with a Canadian Predictive Analytics Lead and a hybrid data team to develop, test, refine, and operationalize Python-based predictive models supporting forecasting, profitability planning, scenario modelling, and what-if analysis.

Responsibilities:
- Develop and test predictive models using Python, statistical methods, and machine learning techniques.
- Support the development of a new predictive cost model for financial forecasting and profitability planning.
- Perform exploratory data analysis to identify trends, patterns, relationships, anomalies, and potential predictive variables.
- Perform data preparation, transformation, feature engineering, and feature selection.
- Train, test, compare, and refine multiple modelling approaches.
- Support regression, forecasting,



classification, time-series, or other predictive modelling approaches as appropriate.
- Develop scenario modelling and what-if analysis capabilities.
- Evaluate model accuracy, stability, interpretability, and business usefulness.
- Develop model-testing and validation procedures.
- Work closely with senior data scientists and Finance stakeholders to refine model assumptions and analytical requirements.
- Collaborate with data engineers to identify required datasets, transformations, and data-quality improvements.
- Support model operationalization and development of repeatable analytical workflows.
- Develop reusable Python code, notebooks, scripts, and analytical components.
- Document model logic, methodology, assumptions, features, validation results, and limitations.
- Support visualization and communication of analytical findings to technical and business stakeholders.
- Assist with

📌 Data Scientist (México)
🏢 New Value Solutions
📍 México