Overview
Join a leading organisation in the resources sector as a Senior Data Scientist and play a key role in driving operational excellence through data-driven solutions. This is an opportunity to apply cutting-edge machine learning and advanced analytics to real-world challenges across planning, maintenance, and scheduling in a complex environment.
Responsibilities
* Analyse operational and sensor data from machinery to generate insights that support maintenance and planning improvements.
* Conduct root cause analysis and build predictive models to minimise unplanned equipment downtime.
* Develop and deploy machine learning models focused on predictive maintenance, scheduling, and asset optimisation.
* Write and maintain production-quality code that is scalable, efficient, and reliable.
* Design optimisation algorithms to improve task prioritisation and resource allocation.
* Collaborate with engineers, planners, and product managers to identify problems and deliver data-driven solutions.
* Work with data engineering and IT teams to integrate models and ensure smooth deployment in cloud environments.
* Support the design and delivery of digital products for planning and scheduling use cases.
* Lead discovery sessions to understand business challenges, define scope, and prioritise based on impact.
* Improve model accuracy and product performance using analytics and user feedback.
Skills and Experience
* 5+ years of experience in data science, machine learning, or advanced analytics with demonstrated experience with maintenance domain data in industrial or resources environments.
* Strong proficiency in Python or R and machine learning libraries.
* Experience working with SQL, big data platforms, and cloud environments.
* Exposure to Snowflake (certification highly regarded).
* Ability to write production-ready, maintainable code and deploy models at scale.
Please reach out to for a confidential chat about the role.