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Data Scientist

Faites partie des premiers candidats.
Motolite
Bulacan
PHP 800 000 - 1 200 000
Faites partie des premiers candidats.
Hier
Description du poste

The Data Scientist in Industry 4.0 Transformation will play a pivotal role in driving data-driven innovation, utilizing advanced analytics and machine learning to optimize manufacturing processes, improve operational efficiency, and support the digital transformation of the organization. This role involves leveraging data science, AI, and IoT technologies to implement smart manufacturing solutions, predictive maintenance, quality control improvements, and supply chain optimization in line with Industry 4.0 principles.

Job Location: Philippine Batteries Inc., Santa Maria Industrial Park, Barangay Bulac, Santa Maria, Bulacan

Key Responsibilities:

  • Develop and implement data-driven solutions that support the digital transformation of manufacturing operations, including predictive maintenance, real-time process optimization, and quality control.
  • Utilize machine learning, artificial intelligence, and advanced analytics to analyze large datasets from IoT-enabled devices, sensors, and production systems.
  • Design and deploy predictive models to identify trends, anomalies, and optimize production schedules, reducing downtime and improving throughput.
  • Collaborate with cross-functional teams (operations, engineering, IT, etc.) to identify key challenges and opportunities for automation, smart production, and data-driven decision-making.
  • Analyze manufacturing performance data to identify bottlenecks, inefficiencies, and areas for improvement in production lines and supply chain processes.
  • Create and maintain dashboards, reports, and visualizations that communicate data insights to both technical and non-technical stakeholders.
  • Implement Industry 4.0 technologies like IoT, AI, machine learning, and robotics to enhance operational capabilities and drive continuous improvement.
  • Contribute to the development and execution of digital transformation roadmaps, ensuring alignment with business goals and the broader Industry 4.0 vision.
  • Optimize data collection, storage, and processing methodologies to ensure clean, high-quality datasets for analysis.
  • Stay up-to-date with the latest trends in Industry 4.0 technologies, data science, and manufacturing innovations.

Requirements:

  • Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, or a related field.
  • Proven experience in data science, machine learning, and analytics, preferably in a manufacturing or industrial setting.
  • Strong knowledge of Industry 4.0 concepts, including IoT, smart manufacturing, automation, and digital twins.
  • Expertise in data manipulation and analysis using tools like Python, R, SQL, or similar programming languages.
  • Experience with machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn) and data visualization tools (e.g., Power BI, Tableau).
  • Familiarity with cloud platforms (AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark).
  • Knowledge of data engineering concepts such as ETL processes, data warehousing, and database management.
  • Strong problem-solving skills and the ability to work in a fast-paced, cross-functional team environment.
  • Excellent communication skills with the ability to translate complex data insights into actionable business strategies.

Desirable Skills:

  • Experience in implementing AI/ML solutions for predictive maintenance, quality control, or supply chain management in manufacturing.
  • Knowledge of cybersecurity and data privacy principles in an industrial IoT context.
  • Experience with robotics, automation systems, and ERP/PLM systems in a manufacturing environment.
  • Familiarity with statistical process control (SPC), lean manufacturing, and Six Sigma methodologies.
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* Le salaire de référence se base sur les salaires cibles des leaders du marché dans leurs secteurs correspondants. Il vise à servir de guide pour aider les membres Premium à évaluer les postes vacants et contribuer aux négociations salariales. Le salaire de référence n’est pas fourni directement par l’entreprise et peut pourrait être beaucoup plus élevé ou plus bas.

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