Senior Data Scientist: Industrial Analytics for Mobility

Magna International

Ramos Arizpe

On-site

MXN 900,000 - 1,300,000

Full time

6 days ago

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Job summary

Magna Powertrain is seeking a Senior Data Scientist to drive data-driven decision-making across manufacturing and engineering operations at our Ramos Arizpe plant. You will leverage advanced analytics, machine learning, and statistical modeling to optimize production processes, improve product quality, and support digital transformation initiatives.

This high-impact role collaborates with cross-functional teams including manufacturing, quality, engineering, and IT, and requires strong

Qualifications

BS or MS (PhD preferred) in Data Science, Statistics, CS, Engineering, or related field.
5+ years in data science, preferably in manufacturing or industrial environments.
Strong proficiency in Python or R and ML frameworks (scikit-learn, TensorFlow, PyTorch, Jupyter).
Experience with SQL databases and big data tools (Spark is a plus).
Hands-on time-series analysis, predictive modeling, and optimization.
Familiarity with MES, PLC data, IoT platforms desirable.
Experience with data visualization tools (Power BI, Tableau, Grafana).
Experience with data engineering (Databricks, Microsoft Fabric), cloud platforms (Azure, AWS) and deployment pipelines.
Solid understanding of statistics, A/B testing, and experimental design.
Strong communication skills and ability to translate insights into business value.
Fluent in Spanish (mandatory) and professional working proficiency in English.

Responsibilities

Develop and deploy machine learning models to optimize manufacturing processes, predictive maintenance, and quality control.
Analyze large-scale structured and unstructured datasets from production systems (MES, ERP, IoT sensors).
Design and implement data pipelines and feature engineering workflows for industrial data.
Identify patterns, trends, and root causes to support continuous improvement of business processes.
Build dashboards and visualizations to communicate insights to stakeholders (Power BI, Tableau, Grafana, etc.).
Collaborate with engineering teams to integrate analytics solutions into production environments.
Lead experimentation and hypothesis testing to improve operational efficiency.
Mentor junior data scientists and analysts, promoting best practices in analytics and coding.
Ensure data governance, quality, and compliance with company standards.