You will report directly to our Director Data Science and Transformation, and you will work out of our Monterrey, Mexico location on a hybrid work schedule.

YOU MUST HAVE
- Minimum of 10-12 years of experience in data engineering, analytics or data science, including a minimum of 5 years directly leading technical teams including hiring, developing and managing performance.
- Hands-on experience designing and operating production data pipelines on a cloud platform, including cost management, with current working proficiency in SQL and Python.
- Experience building and deploying predictive models in production — classification, regression, gradient boosting or time-series forecasting including validation against presente outcomes and monitoring after deployment.
- Demonstrated ability to diagnose why a business metric is underperforming and identify the specific segment driving it, and to present that to senior leaders with a recommendation.
- Experience owning a recurring monthly or quarterly reporting cycle with fixed deadlines,



including reconciliation to financial reporting and sign-off with Finance.
- Fluency in English and Spanish, written and spoken.

WE VALUE
- Bachelor’s degree in Engineering, Computer Science, Information Systems or a related discipline. Advanced degree is a plus.
- Experience with Microsoft Azure and Databricks, Power BI and PostgreSQL.
- Background in manufacturing, supply chain, procurement or cost engineering, with an understanding of how productivity and savings translate into margin.
- Familiarity with continuous improvement methods such as Lean or Six Sigma.
- Experience operating machine learning models in production, including monitoring and retraining.
- Experience building a Center of Excellence or shared service function from an early stage
- Demonstrated ability to present to senior leadership and translate technical detail into business recommendations.

Track record of developing engineers into more senior roles.

LI-Hybrid
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📌 Sr Data Science Manager (Monterrey)
🏢 Honeywell
📍 Monterrey