Continuous Improvements Specialist - Sandton, South Africa - AECI

Description

• Utilising advanced analytics to analyse large datasets and extract meaningful insights.
• Interpreting data trends and patterns to identify areas for improvement.
• Big data mining from multiple areas within AECI Mining
• Investigate centralised data warehousing solution based on preferred technologies
• Automate existing manual data ingestion processes
• Develop ETL/ELT solutions to prepare data for further analysis
• Report writing and preparation of presentations
• Collaborating with operational teams to identify processes that can be optimised.
• Developing data-driven strategies to streamline workflows and enhance overall efficiency.
• Implementing predictive modeling techniques to forecast equipment performance, maintenance needs, and potential issues.
• Providing insights for proactive decision-making and resource allocation.
• Leading and supporting continuous improvement projects based on data-driven findings.
• Implementing data-driven solutions to address operational challenges and enhance performance.
• Perform data analysis and provide recommendations for improvement based on client scope
• Day-to-day business operations support as necessary
• Support continuous business improvement and change management
• Conducting root cause analysis of operational issues and inefficiencies.
• Identifying underlying factors contributing to challenges and recommending corrective actions.
• Developing and implementing systems for real-time monitoring of key performance indicators.
• Alerting stakeholders to deviations from established benchmarks.
• Ensuring the accuracy and reliability of data through effective data governance practices.
• Implementing measures to improve data quality and integrity.
• Collaborating with various departments, including operations, maintenance, and safety, to gather relevant data and insights.
• Facilitating communication and knowledge sharing to drive continuous improvement.
• Implementing automation tools and technologies to streamline data collection and analysis.
• Introducing efficiency measures based on data-driven recommendations.
• Providing training and guidance to operational teams on interpreting and using data for continuous improvement.
• Facilitating knowledge transfer on best practices in data-driven decision-making.