Data Scientist Manager

Cognite Cognite · Industrial · UK England, Netherlands · Value Delivery

Manager for a Data Science team in Europe, focusing on industrial digitalization and AI solutions. The role involves leading, coaching, and developing the team, providing technical leadership in ML and GenAI, driving customer project delivery, and ensuring best practices in model development and deployment. Experience in industrial sectors and MLOps is highly desirable.

What you'd actually do

  1. Lead, coach, and develop a team of Data Scientists across Europe, fostering a culture of collaboration, innovation, and continuous learning.
  2. Provide technical leadership and guidance on data science methodologies, machine learning, optimization, and GenAI applications.
  3. Drive the successful delivery of customer projects, ensuring high-quality outcomes and scalable solutions.
  4. Partner with customers and stakeholders to understand business challenges, lead discovery workshops, and identify opportunities where data science can create measurable value.
  5. Support the development and deployment of scalable solutions for customer use cases across Oil & Gas, Manufacturing, and Power & Utilities.

Skills

Required

  • Python
  • SQL
  • modern machine learning frameworks
  • deploying machine learning solutions into production
  • Generative AI technologies
  • cloud platforms (AWS, Azure, or Google Cloud Platform)
  • software engineering principles
  • MLOps practices
  • Git
  • leadership skills
  • communication skills

Nice to have

  • industrial sectors such as Oil & Gas, Energy, Manufacturing, Asset Performance Management, Reliability, Maintenance, or Production Optimization

What the JD emphasized

  • leading, managing, and developing technical teams
  • deploying machine learning solutions into production environments
  • leveraging Generative AI technologies
  • MLOps practices

Other signals

  • leading a team of data scientists
  • delivering data-driven solutions
  • driving technical excellence
  • customer engagements
  • shaping data science strategy
  • developing and deploying scalable solutions
  • leveraging Generative AI technologies
  • MLOps practices