South32 is a globally diversified mining and metals company. Our purpose is to make a difference by developing natural resources, improving people’s lives now and for generations to come. We are trusted by our owners and partners to realise the potential of their resources. We produce bauxite, alumina, aluminium, metallurgical coal, manganese, nickel, silver, lead and zinc at our operations in Australia, Southern Africa and South America. With a focus on growing our base metals exposure, we also have two development options in North America and several partnerships with junior explorers around the world.
The Opportunity
Reporting to the Data Science Lead, the Specialist Data Scientist will be responsible for championing the identification, development, implementation and adoption of Data Science to improve the safety, production and cost of Operations / Functions.
Accountabilities Include:
- Uphold the South32 values and apply the Code of Business Conduct in all activities
- Actively participate in the Business Intelligence & Analytics team activities and contribute to the improvement / advancement of the team
- Build strong relationships within the business to ensure a true understanding of the improvement areas
- Influence the Data Science roadmap and framework in alignment to the I&BO Function strategy
- Stay up to date with emerging technologies and attend relevant forums
- Deliver on Data Science requirements and projects
- Provide coaching and guidance to the broader business in Data Science methodologies
- Adopt and implement Data Science mindsets, practices and frameworks across relevant projects
Qualifications
- Relevant tertiary qualification such as a Bachelors or Master’s degree in STEM (Mathematics / Statistics / Computer Science/ Physics preferred).
- MSc or PhD in a quantitative discipline (Statistics, Data Mining, Machine Learning) highly regarded.
Technical/Specialist Skills
- Advanced statistical and data science skills in data manipulation, statistical modelling and machine learning
- Advanced R, Python and SQL experience
- Experience with Kubernetes, Docker and containerisation
- Experience of Tableau, Power BI or other reporting platforms
- Experience using Sensor data, Scada, HMI, Historian, MES, ERP and typical applications within the industrial sector
- Demonstrated production deployment of models using online / live data streams