Brazil Job Openings

Kinross Gold Corporation

Machine Health Maintenance Supervisor (BR)

September 15, 2024

We ask all applicants to submit their resumes in English for this role.


Who We Are


Kinross is a Canadian-based global senior gold mining company with operations and projects in the United States, Brazil, Mauritania, Chile and Canada. Our focus on delivering value is based on our four core values of Putting People First, Outstanding Corporate Citizenship, High Performance Culture, and Rigorous Financial Discipline. Kinross maintains listings on the Toronto Stock Exchange (symbol:K) and the New York Stock Exchange (symbol:KGC).



Mining responsibly is a priority for Kinross, and we foster a culture that makes responsible mining and operational success inseparable. We also achieved record high levels of local employment, with 99% of total workforce from within host countries, and advanced inclusion and diversity targets, including instituting a Global Inclusion and Diversity Leadership Council.


Eager to know more about us? Visit Home - Kinross Gold Corporation



Job Description


Responsible for leading a maintenance team that consists of Machine Learning (ML) analysts for Kinross Gold, tracking and communicating progress upwards to the company and its sites, maintaining vendor relations, and occasionally stepping in to cover for their analysts' roles in communicating or fixing automated alerts as needed. Requires communication with multiple sites across the globe and the lead of two direct reports.



Job Responsibilities


  • Facilitate communication to upper management across all sites to ensure engagement and compliance from plant and mobile maintenance teams.
  • Manage expectations and results of the Machine Health Maintenance Team (MHMT).
  • Lead and support the MHMT in developing accurate alerts from the given ML software.
  • Lead and support the MHMT in developing new processes and standards to best improve the solution.
  • Communicate with Kinross sites to effectively and timely support machine health optimization efforts.
  • Understand the software results well enough to efficiently communicate efforts and issues with sites and technology providers.
  • Help create, maintain, and send reports as deemed necessary for each branch of communication and alert tracking.
  • Develop and optimize analysis procedures to improve alerts and analytic practices.
  • Be able to determine the best practices to keep with each individual site and team, and willing to re-evaluate and change those as the project and sites grow.
  • Regular attendance / communication required.
  • Compliance with all company policies and procedures including but not limited to: safety, confidentiality, and environmental policies.
  • Meet or exceed established performance expectations set by Management.
  • Possession of all documents required for employment by Kinross.
Education and Experience


  • Bachelor’s degree or similar certification in mining or maintenance fields.
  • Engineering, process optimization and programming-adjacent degrees with experience in maintenance or mining is also suitable.
  • Experience in leadership and project management.
  • Certifications or previous courses in leadership preferred.
  • Ability to perform and understand statistical analyses and mathematical modelling related to ML.
  • General knowledge of mining methods and operating practices related to Maintenance and Reliability.
  • Optional experience with mining solutions such as Mine Star Health, Modular Mine Care, Wenco Readyline, or OSI PI.
  • Ability to track team progress, observe growth opportunities, and continuously work to optimize ML existing systems while looking for ways to test, create, and build more.
  • Must be able to apply good verbal, written, and interpersonal communications skills that will facilitate efficient and professional interaction with multiple departments over mining and maintenance related terms in English across sites globally. Fluency in Portuguese, Spanish, or French would be beneficial.
  • Ability to train employees in the use of the ML tools used and alerting process.
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