As the Data Scientist, your responsibilities will include:

Role Overview

- Lead data science initiatives within the Digital Operations team, driving innovation and operational excellence across Supply Chain, Manufacturing, and Quality.
- Manage and mentor citizen data scientists while spearheading complex data science projects from inception to deployment, ensuring continuous alignment with business objectives.

Leadership and Project Management

- Lead and manage citizen data scientists through all phases of data science projects, providing mentorship and guidance.
- Collaborate with cross-functional teams to design, scope, and prioritize data science projects, including defining data collection methods, modeling techniques, and expected outcomes.
- Manage data science projects from initiation to completion, continuously revisiting and refining models to ensure they meet evolving business needs.
- Develop and maintain governance principles for data science projects, ensuring best practices are followed.

Problem Analysis and Project Management

- Develop advanced analytics models (predictive, prescriptive, machine learning, simulation, statistical) to address complex business challenges in Supply Chain, Manufacturing, and Quality.
- Utilize advanced machine learning and statistical techniques to perform data discovery, uncovering new correlations and interdependencies among variables that can drive operational improvements.
- Lead the development of scalable data pipelines and integrate model performance management tools into existing business infrastructure.

Data Collection, Exploration, and Integration

- Access and integrate data from various sources,



including SQL databases and other systems relevant to Digital Operations.
- Conduct data cleaning, transformation, and preprocessing to ensure data quality and readiness for modeling.
- Apply statistical analysis, such as hierarchical clustering and PCA, to uncover insights.
- Aid in the creation of data pipelines for more efficient and repeatable data science projects
- Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering and principal components analysis (PCA)
- Develop classification and regression models or apply unsupervised learning to aid in uncovering insights in data.

Operationalization

- Develop advanced analytics models (predictive, prescriptive, machine learning, simulation, statistical) to address complex business challenges in Supply Chain, Manufacturing, and Quality.
- Utilize advanced machine learning and statistical techniques to perform data discovery, uncovering new correlations and interdependencies among variables that can drive operational improvements.
- Lead the development of scalable data pipelines and integrate model performance management tools into existing business infrastructure.
- Collaborate with IT and data engineering teams to deploy and monitor production ML models, establishing best practices around ML production infrastructure.




- Continuously monitor, revisit, and refine deployed models to ensure they remain aligned with business objectives and adapt to changing operational needs.
- Work closely with stakeholders to communicate findings, insights, and recommendations effectively, ensuring that data-driven strategies are integrated into decision-making processes.

Other

- Stay updated with the latest advancements in data science, machine learning, and AI, and proactively integrate these innovations into projects where applicable.
- Drive strategic initiatives by identifying and prioritizing AI/ML opportunities that align with the organization’s operational goals, challenging the status quo, and promoting bold, innovative thinking.

The Data Scientist position is well-suited for you if you:

- Can translate business strategies into actionable plans by leveraging market and functional knowledge
- Champion new processes, remove barriers, and adapt current processes to facilitate improvement
- Build sustainable internal and external relationships that deliver value for the business
- Cultivate and maintain partnerships across functions, helping teams successfully navigate competing priorities
- Challenge the status quo and promote bold thinking to create value

Qualified candidates will have:

- Bachelor’s Degree in Business, Management Information Systems, Data Science, or a related field required.
- Master’s Degree in Data Science field strongly preferred.
- Proven experience in leading and managing citizen data scientist.
- Specialization in ML, AI, cognitive science, or data science
- Knowled

📌 Data Scientist (Ciudad de México)
🏢 Ingredion
📍 Ciudad de México