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, Industry 4.0 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.
Work Appropriately
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On-Site : This position requires full-time on-site work.
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Availability to work rotating shifts when required by operational needs.
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, Industry 4.0, 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 balancing, capacity analysis, throughput, material flow, and constraint analysis.
- Experience with Lean Manufacturing, Six Sigma, Operational Excellence, and structured problem-solving methodologies.
Core Competencies
- Advanced analytical thinking and the ability to solve complex business and technical problems.
- Strong understanding of data, artificial intelligence, machine learning, and digital technologies.
- Ability to convert operational needs into scalable data and AI solutions.
- Systems thinking and a strong results orientation.
- Effective communication with technical, manufacturing, and leadership teams.
- Technical leadership and the ability to influence without formal authority.
- Collaborative approach when working with global and cross-functional teams.
- Strong organization, autonomy, and priority-management skills.
- Innovation, continuous learning, and a commitment to continuous improvement.
- Ability to explain complex data, analytical, and AI concepts to non-technical audiences.
If you require any reasonable accommodation to continue your application process, please inform your recruiter.
Please remember to attach your resume/CV when applying for this position.
Diversity and inclusion are our strengths. We respect and value what each individual contribution to our team, including their origin, education, sex, race, ethnic group, sexual orientation, gender expression and / or identity, religious context, age, generation, and disability. We believe that our ability to meet the needs and expectations of an increasingly diverse and global customer base is closely linked to the diversity and inclusion that we experience within General Motors.
Ce poste exige le travail en présentiel. Cela signifie que le candidat retenu devra se rendre à un site précis de façon permanente.
Renseignements sur la diversité
General Motors est résolue à être un lieu de travail qui est non seulement exempt de discrimination illégale, mais aussi un endroit qui favorise véritablement l'inclusion et l'appartenance. Nous sommes convaincus que la diversité de la main-d'œuvre permet de créer un environnement dans lequel nos employés peuvent s'épanouir et développer de meilleurs produits pour nos clients. Nous encourageons les candidats intéressés à consulter les principales responsabilités et compétences requises pour chaque rôle et à postuler à tout poste qui leur correspond. Dans le cadre du processus de recrutement, les candidats peuvent devoir, le cas échéant, réussir une évaluation liée au poste ou une présélection d'emploi avant d'être embauchés. Pour en savoir plus, consultez notre processus de recrutement.
Déclaration concernant l'égalité d'accès à l'emploi (É.-U.)
General Motors est fière d'être un employeur souscrivant au principe de l'égalité d'accès à l'emploi. Tous les candidats qualifiés seront pris en compte, sans égard à la race, à la couleur, à la religion, au sexe, à l'orientation sexuelle, à l'identité de genre, à l'origine ethnique, aux situations de handicap ou au statut protégé d'ancien combattant.
Aménagements (É.-U. et Canada)
General Motors offre des occasions à tous les chercheurs d'emploi, y compris les personnes handicapées. Si vous avez besoin d'un accommodement raisonnable pour vous aider dans votre recherche d'emploi ou la soumission de votre candidature, envoyez-nous un courriel à l'adresse [email protected] ou appelez-nous au 800 865-7580. Veuillez inclure dans votre courriel une description spécifique du type d'accommodement demandé, ainsi que le titre d'emploi et le numéro de demande du poste auquel vous postulez.
