Reporting to the Manager, Global Customer Experience, in the Consite Mine PoV team, theData Analyst will be a subject matter expert in interpreting data and communicating insights on the performance and health of heavy mining equipment. You will collaborate with business stakeholders to understand their questions and leverage data to provide meaningful answers and solutions. This may involve the development of new data products to answer existing and emerging business challenges. You will gain an in-depth understanding of diverse data sets related to equipment performance and determine the best methods for processing and visualizing this data. Your work will facilitate action and assist end users in deriving value from available data.
Key Deliverables and Responsibilities: Data Collection and Preparation: Collaborate with cross-functional teams to gather data from various sources. Develop data products and ensure data quality and consistency for analysis. Data Analysis and Modelling: Utilize advanced statistical and machine learning techniques to analyse 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. Experiment Designs and Results: Create plans and desired outcomes of studies that test the effects of different variables or interventions on asset health and productivity outcomes. May include experimental setups, data collection methods, statistical tests, and conclusions. Dashboards and Applications: Create interactive tools that allow users to access, explore, and manipulate pre-aggregated and organised data products. May include graphs, charts, tables, filters, sliders, and other widgets that enable data visualization and user interaction. Analysis Reports: Make documents or presentations that summarize the findings and insights from data exploration and analysis. May include descriptive statistics, visualizations, hypotheses, and recommendations for further actions or improvements. Data Models: Develop machine learning, statistical and logical based models to produce outputs, predictions, classification, or recommendations. They may also include the data preprocessing and postprocessing steps. Experience and Knowledge Bachelor or higher degree in Statistics, Data Science, Mathematics, Engineering or similar. Strong background in data exploration, statistics, data visualization, communication and problem-solving Able to define the problem, scope the project, plan the resources, monitor the progress, evaluate the results, and deliver the solutions. Experience in SQL is essential Experience with Grafana is a strong plus Experience with visualisation libraries is a plus (Plotly, Matplotlib etc.) Experience in using data on cloud computing, and big data platforms Knowledge in data quality management practices, ensuring compliance and accuracy in data handling. Experience in heavy industry is a plus Fluency in English is a must, Japanese language ability is a plus. Travel of up to 10% may be required (must have a valid passport and legally be able to travel internationally if required) Skills and Abilities Proactive technical problem solver. Understand business context, objectives, and impact of their work. 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.
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