Job description

Talent International is searching for multiple experienced Data Scientist to join our client, a large mining company. This role is based in Eight Mile Plains on a permanent basis.

// Permanent Role

// 2 Days WFH Per Week

// Eight Mile Plains, Brisbane Location

About The Role

The data scientist will be the subject matter expert (SME) in extracting valuable insights using advanced statistical models and machine learning techniques on Big Data in Cloud Computing Environments. You will work closely with business stakeholders to understand their goals and determine how the available data can be used to achieve those goals. In collaboration with technology development teams and 3rd party ecosystem partners, you will design data pipeline requirements and data modeling processes, create algorithms and predictive models to extract the information the business needs. Help analyze the data and share meaningful insights with peers. Will gain understanding of target data sets and how it should be pre-processed for reliable and scalable analytic output. Seek comprehensive definition on user requirements to ensure Analytics product meets expectations efficiently as possible, avoiding multiple iterations and/or re-work.


  • Data Pipeline and Data Warehouse design, in collaboration with technology development partners
  • Data Collection and Preparation: Collaborate with cross-functional teams to gather data from various sources. Develop data pipelines and ensure data quality and consistency for analysis.
  • Data Analysis and Modeling: Utilize advanced statistical and machine learning techniques to analyze large datasets and identify patterns, trends, and anomalies. Build predictive models to optimize mining operations and equipment maintenance.
  • Visualization and Reporting: Create data visualizations and reports to communicate findings and insights to stakeholders, including management and operational teams. Develop interactive dashboards for real-time monitoring of mining processes.
  • Optimization and Efficiency: Work closely with engineers and mining experts to identify areas for improvement in operational efficiency of equipment. Collaborate on the development of algorithms and tools for automated decision support.


Experience and Knowledge

  • Strong background in programming, statistics, machine learning, data visualization, communication and problem-solving
  • Experience in designing and implementing high performance data pipelines, warehouse and analytics systems on common cloud platforms (e.g. AWS)
  • Proficient with data mining, cleaning, visualization, and programming languages such as Python, R, SQL, Java, JavaScript.
  • Experience in using data on cloud computing, and big data platforms
  • Able to define the problem, scope the project, plan the resources, monitor the progress, evaluate the results, and deliver the solutions.
  • Fluency in English is a must, Japanese is a plus

Skills & Abilities

  • Proactive technical problem solver, with strong ability to map technologies to business priorities.
  • Understand business context, objectives, and impact of their work, and adhere to the ethical principles and standards of data science.
  • Communicate clearly and effectively with different audiences, such as technical peers, business analysts, managers, and customers.
  • Proven self-starter with ability to turn objectives into actions and results.
  • Present their findings and recommendations using compelling and engaging visualizations and stories.
  • Think critically and creatively and generate new ideas and insights from data.
  • Contribute to a team environment towards common goals, be open to work sometimes outside of comfort zone to meet objectives.


  • Bachelor or higher degree in Computer Science, Mechatronics, Mathematics or Engineering.
  • Travel of up to 10% may be required (must have a valid passport and legally be able to travel internationally if required)

How To Apply

To find out more, please “Apply for this job” or contact James Grierson or Mats Rorvik on (07) 3031 4522 // For a list of all vacant positions, please see our website

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