Lead Data Scientist - ML, Analytics & Operations Impact

Ingredion Incorporated; Región Centro; Presencial; MXN 1.200.000 - 1.800.000; Jornada completa

Descripción de la vacante

Ingredion Incorporated is seeking a Data Scientist to lead analytics initiatives within its Digital Operations team, spanning Supply Chain, Manufacturing, and Quality. The role includes mentoring citizen data scientists, guiding projects from inception to deployment, and aligning them with business goals.

Responsibilities include developing scalable data pipelines, applying ML and statistics, and collaborating with IT to productionize models while communicating insights to stakeholders.

Formación

• Bachelor’s degree in Business, MIS, Data Science or related field.
• Master’s degree in Data Science strongly preferred.
• Proven experience leading citizen data scientists.
• Knowledge of agile methodologies and ML/data science applications to business.
• Experience deploying ML models in production and communicating results.

Responsabilidades

• Lead data science initiatives within Digital Operations across Supply Chain, Manufacturing, and Quality.
• Manage and mentor citizen data scientists on complex projects from inception to deployment.
• Collaborate with cross-functional teams to define data collection, modeling techniques, and outcomes.
• Develop scalable data pipelines and integrate model performance tools.
• Monitor deployed models and communicate insights to stakeholders.

Conocimientos

Data science

Machine learning

Leadership

Project management

Communication

Mentorship

Data governance

Educación

Bachelor’s degree in Business, MIS, or Data Science

Master’s degree in Data Science (preferred)

Herramientas

SQL databases

ML deployment tools

Descripción del empleo

Ingredion Incorporated is seeking a Data Scientist to lead analytics initiatives within its Digital Operations team, spanning Supply Chain, Manufacturing, and Quality. The role includes mentoring citizen data scientists, guiding projects from inception to deployment, and aligning them with business goals.

Responsibilities include developing scalable data pipelines, applying ML and statistics, and collaborating with IT to productionize models while communicating insights to stakeholders.