Ingeniero Industrial con especialidad en IA y Data Analytics

Job Description What You Will Do?

The primary purpose of this role is to leverage data, artificial intelligence, and digital technologies to improve manufacturing performance, eliminate operational waste, and support data-driven decision-making. The position will transform manufacturing data into actionable insights, develop analytical and AI-based solutions, and implement digital applications that improve productivity, quality, capacity, throughput, and resource utilization. The ideal candidate combines strong capabilities in data engineering, analytics, machine learning, software development, and Industrial Engineering. This role requires the ability to work in a dynamic, fast-paced manufacturing environment and collaborate with technical, manufacturing, maintenance, and leadership teams.

Key Responsibilities

• Identify opportunities to apply artificial intelligence, machine learning, advanced analytics, and automation to manufacturing and operational challenges.
• Collect, integrate, clean, and analyze data from manufacturing systems, MES platforms, equipment, processes, and other sources.
• Develop analytical models, machine learning solutions, dashboards, applications, and automations that support operational decision‑making.
• Translate manufacturing and business requirements into scalable data and digital solutions.
• Develop and maintain data pipelines, analytical datasets, and performance‑monitoring tools.
• Create metrics and dashboards to monitor schedule progress, production performance, throughput, quality, capacity, constraints, and risk areas.
• Analyze manufacturing data to identify patterns, bottlenecks, anomalies, root causes, and opportunities for improvement.
• Apply predictive and prescriptive analytics to support maintenance, quality, production planning, material flow, and process optimization.
• Use simulation, optimization, and data-driven methodologies to improve the sequence of operations, workflow, line balancing, and resource allocation.
• Support the development and analysis of Manufacturing Master Schedules using data and critical path methodology.
• Develop crew plans and analytical tools to help ensure resources are properly allocated and utilized effectively.
• Design solutions that reduce waste related to time, cost, materials, labor, machine utilization, energy, and other non-value-added resources.
• Leverage MES, Industry4.0 technologies, automation, connected systems, and manufacturing data platforms to enable digital transformation.
• Support structured problem solving through Lean Manufacturing, Six Sigma, Operational Excellence, and other continuous improvement methodologies.
• Manage technical projects from requirements definition through deployment, adoption, and continuous improvement.
• Provide technical support and explain analytical and AI solutions to manufacturing, maintenance, production and leadership teams.
• Communicate complex technical concepts and data-driven recommendations to both technical and non-technical audiences.

Required Qualifications

• Bachelor's degree in Data Science, Computer Science, Software Engineering, Computer Engineering, Systems Engineering, Industrial Engineering, Electronics Engineering, or a related field.
• Five to eight years of professional experience in data analytics, data engineering, artificial intelligence, machine learning, software development, IT, digital transformation, Industrial Engineering, or a related area.
• Demonstrated experience developing data products, analytical models, machine learning solutions, dashboards, applications, or automations.
• Practical proficiency in Python, SQL, Java, machine learning, data analysis, and web development.
• Experience working with data integration, data pipelines, databases, APIs or cloud-based data environments.
• Experience managing technical projects from initial requirements through implementation and deployment.
• Ability to analyze complex datasets and convert findings into actionable business and manufacturing recommendations.
• Intermediate-to-advanced technical English proficiency.
• Experience working in a manufacturing or operations environment.

Preferred Qualifications

• Experience applying artificial intelligence, machine learning, or advanced analytics in manufacturing, supply chain, quality, maintenance, or operations.
• Experience in automotive assembly or other automotive manufacturing environments.
• Knowledge of MES, Industry4.0, automation, manufacturing systems, and connected equipment.
• Experience with predictive maintenance, computer vision, anomaly detection, optimization, simulation, or time-series analysis.
• Knowledge of Industrial Engineering practices, including time studies, standard work, line balanc