Senior Data Analyst

PURPOSE & OBJECTIVE The Senior Data Analyst
- Mining Technical Services is responsible for developing advanced analytics, predictive models, optimization solutions, and data-driven insights that enhance operational performance across mining technical disciplines. The role partners closely with Technical Services teams, including Mine Planning, Geology, Resource Modelling, Grade Control, Geotechnics, Hydrogeology, Drill & Blast, and Survey, to transform operational and geological data into actionable intelligence. The position plays a critical role in accelerating Endeavour's data-driven mining strategy by leveraging statistical analysis, machine learning, forecasting, and decision-science techniques to improve productivity, resource utilization, recovery, operational planning, and business outcomes. The role bridges Technical Services and Data & Insights, ensuring analytical solutions are scalable, governed, and aligned with enterprise data standards and architectures. KEY ACCOUNTABILITY
• Design, develop, and deploy advanced analytical models supporting Technical Services operations.
• Apply statistical analysis, machine learning, forecasting, and optimization techniques to solve complex mining challenges.
• Develop predictive models for operational performance, resource estimation, or reconciliation, equipment productivity, and planning accuracy.
• Transform complex operational datasets into business insights that support data-driven decision making.
• Develop reusable analytics products and decision-support tools.
• Build scalable analytical workflows leveraging Python, SQL, Snowflake, and cloud-based analytics platforms.
• Automate data processing, model execution, and insight generation where possible.
• Support integration of structured and unstructured mining data sources.
• Identify opportunities to improve operational efficiency through data science techniques.
• Develop scenarios and optimization models supporting mine planning, pit optimization, production forecasting resource modelling, grade control, drill & blast performance, cost optimization, while delivering recommendations supported by quantitative evidence and measurable business value.
• Explore and implement AI solutions that enhance operational performance and decision making.
• Evaluate opportunities for generative AI, machine learning, anomaly detection, forecasting, and predictive maintenance. Collaborate with Data Engineers and Information Technology teams to operationalize analytical solutions.
• Support enterprise AI governance and responsible AI practices by developing executive-level dashboards and analytical products in Power BI, translating sophisticated analytical findings into clear and actionable business recommendations, presenting insights into Technical Services leadership and operational stakeholders and by supporting strategic planning through scenario analysis and predictive forecasting.
• Ensure analytical models are built on trusted and governed datasets, Promote data quality standards and best practices across Technical Services. Define business rules, metadata, and analytical documentation.
• Contribute to enterprise data governance initiatives in partnership with the Data & Insights team.
• Act as the primary analytics advisor to Technical Services leadership through engaging stakeholders to identify high-value use cases and analytics opportunities, mentoring junior analysts , promoting analytical capability development and fostering adoption of data-driven decision making throughout Technical Services. SKILLS, KNOWLEDGE & EXPERIENCE

Education:
• Master's degree in one of the following disciplines: Data Science Statistics, Computer Science, Applied Mathematics, Data Engineering, Operations Research, Mining Engineering with strong analytics specialization. Relevant

experience:
• Mining, geological, or industrial experience is strongly preferred.
• Minimum 7 to 10 years of experience in data science, advanced analytics, or industrial analytics.
• Demonstrated experience delivering business value through predictive analytics and machine learning solutions.
• Experience within mining, natural resources, engineering, manufacturing, or heavy industry is highly desirable.
• Experience working in both business and technical environments
• Analytics & Data Science: Advanced statistical modelling; Machine Learning; Predictive Analytics; Time Series Forecasting; Optimisation Techniques; Feature Engineering; Model Validation and Monitoring
• Programming: Python (Advanced); SQL (Advanced); Snowflake; Git; APIs and data integration concepts
• Data Visualisation: Advanced Power BI; DAX; Power Query; Storytelling with Data
• Cloud & Data Platforms: Snowflake; Azure Data Platform; Databricks (advantageous); MLOps concepts; Enterprise data architectures