This is a high-impact position that collaborates closely with cross-functional teams including manufacturing, quality, engineering, and IT.
Key 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.
Qualifications
Bachelor’s or master’s degree (PhD preferred) in Data Science, Statistics, Computer Science, Engineering, or related field.
5+ years of experience in data science, preferably within manufacturing or industrial environments.
Strong proficiency in Python or R and experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch, Jupyter).
Experience working with SQL databases and big data tools (e.g., Spark is a plus).
Hands-on experience with time-series analysis, predictive modeling, and optimization.
Familiarity with manufacturing systems (MES, PLC data, IoT platforms) is highly 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 with the ability to translate complex insights into business value.
Fluent in Spanish (mandatory) and professional working proficiency in English
Preferred Skills
Experience in automotive or Tier 1 supplier environments.
Knowledge of Industry 4.0, smart factory, and digital twin concepts.
Background in MLOps and model deployment in production environments.
Awareness, Unity, Empowerment
At Magna, we believe that a diverse workforce is critical to our success. That’s why we are proud to be an equal opportunity employer. We hire on the basis of experience and qualifications, and in consideration of job requirements, regardless of, in particular, color, ancestry, religion, gender, origin, sexual orientation, age, citizenship, marital status, disability or gender identity. Magna takes the privacy of your personal information seriously. We discourage you from sending applications via email or traditional mail to comply with GDPR requirements and your local Data Privacy Law.
AI-Assisted Screening Disclosure
As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our Workday system. These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team. Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.
Under conditions defined by applicable law, you may have the right to request an explanation of how AI is used to support decision-making.
If you have any questions or concerns about this process, feel free to contact our Talent Attraction team.
Worker Type
Regular / Permanent
Group
Magna Powertrain
