Data Scientist for Manufacturing Innovation

3 weeks ago


Glasgow, Glasgow City, United Kingdom Maserati of San Diego Full time

The Maserati of San Diego, a leading international technological institution, collaborates with industry to drive business growth through research and innovation. Our National Manufacturing Institute Scotland (NMIS) supports manufacturing and engineering sectors by advancing productivity and integrating new digital technologies.

As a Data Analyst, you will bridge efforts between NMIS, the University, and industry partners, facilitating collaborative research and development in manufacturing. You can expect to have the responsibilities:

  • Develop and refine data-driven decision support systems using statistical analysis, machine learning, and artificial intelligence.
  • Transform raw data into visual narratives to support decision-making in manufacturing.
  • Create innovative visualization solutions to present manufacturing data clearly and engagingly.
  • Collaborate with data scientists, engineers, and UX designers to transform data into actionable insights.
  • Construct and manage diverse database structures (relational and non-relational).
  • Develop models on remote servers for deployment to edge devices or business intelligence systems.

This role comes with an estimated salary range of $80,000-$110,000 per annum, depending on experience. The role also offers opportunities for ground-breaking research within the manufacturing industry, collaboration with a diverse team of industry, academia, and public sector professionals, and professional growth.

To be successful in this role, you will require:

  • Expertise in statistical analysis, machine learning, and artificial intelligence.
  • Proficiency in designing and managing various database structures.
  • Competence in data exploration and visualization.
  • Experience in crafting data visualizations and dashboards.
  • Experience developing models for deployment to edge devices or BI systems.
  • Excellent collaborative skills for working with interdisciplinary teams.

A minimum of a PhD in Computer Science, Engineering, or Mathematics, or a 2:1 Honors degree with extensive relevant industrial experience is required for this position.



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