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Data Analyser, Wet Plant - S3 at First Quantum Minerals, Solwezi

Data Analyser, Wet Plant - S3 at First Quantum Minerals in Solwezi. Full-time. Apply with swipeandhired.

At First Quantum, we free the talent of our people by taking a very different approach which is underpinned by a very different, very definite culture – the “First Quantum Way”.

Working with us is not like working anywhere else, which is why we recruit people who will take a bolder, smarter approach to spot opportunities, solve problems and deliver results.

Our culture is all about encouraging you to think independently and to challenge convention to deliver the best result. That’s how we continue to achieve extraordinary things in extraordinary locations.

Job description:
Purpose
Reporting to the Snr Project Engineer, the Data Analyst will collaborate with business and operational leaders to provide an impact by leveraging data and analytical tools, strategic thinking, and hypothesis-based analysis. The data analyser will be responsible for continuous register data modelling complex process problems through statistical, algorithmic, mining, and visualization techniques. Further, they will support senior leadership by creating business insights, reports, and analyses to aid in the decision-making process

Key Responsibilities

Develop a thorough understanding of metallurgical processes and processing plant operations, ensuring safe and effective practices.
Monitor, analyze, and optimize plant performance data to improve recovery, throughput, concentrate quality, and operational efficiency.
Identify process bottlenecks, performance losses, and improvement opportunities through data analysis and metallurgical investigations.
Provide technical support and recommendations to Operations and Maintenance teams to enhance plant performance and reliability.
Develop, maintain, and improve metallurgical databases, process reports, dashboards, and performance statistics.
Conduct process modelling, statistical analysis, and data-driven investigations to support operational and strategic decision-making.
Perform metallurgical test work, process evaluations, and large-scale data analysis to identify relationships between process variables.
Develop and maintain mass balances, process flow diagrams (PFDs), and process and instrumentation diagrams (P&IDs).
Apply statistical, visualization, and machine learning tools to enhance process understanding and support continuous improvement initiatives.
Generate and maintain online process monitoring dashboards and reporting tools.
Ensure data quality, integrity, and compliance with company standards and best practices.
Support the deployment, monitoring, and continuous improvement of analytical and predictive models.
Communicate technical findings, recommendations, and process improvement opportunities to stakeholders through reports and presentations.
Support metallurgical accounting activities and provide ad hoc cover when required.
Lead and support process improvement and optimization projects while meeting project milestones and operational targets.
Promote data-driven decision-making and assist stakeholders in the effective use of data and analytical tools.
Perform any other duties as assigned by the Supervisor

Qualifications

Bachelor's Degree in Metallurgy or Mineral Processing.
Qualifications in Data Science, Process ControlComputer Science, Statistics, Process Control, or related analytical disciplines will be an added advantage.
Training or certification in Machine Learning (ML), Artificial Intelligence (AI), Data Analytics, or Process Optimisation would be advantageous.
All Qualifications must be certified by Zambia Qualifications Authority (ZAQA)

Experience

Minimum of 5 years' experience in a large-scale mineral processing plant, with exposure to crushing, grinding, flotation, thickening, and metallurgical accounting processes.
Demonstrated experience in process monitoring, metallurgical troubleshooting, plant optimization, and continuous improvement initiatives.
Minimum of 2 years' experience applying data analytics, statistical analysis, and visualization techniques to support operational decision-making and process improvement.
Proficiency in data analysis and programming tools such as Python, SQL, Power BI, or similar analytical platforms.
Knowledge of statistical techniques including regression analysis, multivariate analysis, process control monitoring, machine learning, and predictive analytics.
Experience in developing process dashboards, production reporting systems, and performance monitoring tools.
Strong analytical, problem-solving, and technical communication skills with the ability to translate data into practical operational improvements.
Experience in process modelling, mass balancing, and metallurgical performance analysis.
Familiarity with simulation and modelling software such as JKSimMet, MetSIM, or similar process simulation tools would be advantageous.
Experience working with plant historians, SCADA, PI System, control systems, and other process data management platforms would be an added advantage

BEHAVIOURAL TRAITS

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Teamwork
Safety Awareness
Boldness
Driven
Good work attendance
Ability to work under pressure

OPERATIONAL REQUIREMENTS

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Computer Literate
Standby duties
Shift duties
Working at Heights
Confined Spaces
Appropriately handle corrosive and toxic substances
Mobile and Moving equipment

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