Remote Mining Data Analyst

About the Role

Our client is seeking a proficient Remote Mining Data Analyst to support their global operations. This fully remote position allows you to leverage your analytical skills from anywhere in the UK, focusing on the interpretation of vast datasets generated from exploration and production activities. You will play a key role in identifying trends, optimizing processes, and providing actionable insights to enhance efficiency and profitability across various mining projects . This role is vital for driving data-informed decision-making within our client's forward-thinking mining business .

Key Responsibilities

• Collect, clean, and analyze large datasets related to mining operations, exploration, and production.
• Develop and maintain dashboards and reports to visualize key performance indicators (KPIs).
• Identify trends, patterns, and anomalies in mining data to provide actionable insights.
• Collaborate virtually with geologists, engineers, and operations managers to understand data needs and deliver relevant analyses.
• Utilize statistical methods and data mining techniques to uncover opportunities for improvement.
• Ensure data integrity and accuracy, implementing quality control measures.

Requirements

• Bachelor's degree in Data Science, Statistics, Computer Science, Mining Engineering, or a related quantitative field.
• Minimum of 3 years of experience as a Data Analyst, with exposure to the mining or resources sector .
• Proficiency in data analysis tools and languages such as Python, R, SQL, and Excel.
• Experience with data visualization tools like Tableau or Power BI.
• Strong analytical and problem-solving skills, with excellent attention to detail.
• Ability to work independently in a remote setting and communicate findings effectively to diverse audiences.

Benefits

• Competitive salary and potential for bonuses.
• Fully remote working arrangement, offering maximum flexibility.
• Comprehensive health and wellness benefits.
• Opportunities for continuous learning and professional development in data analytics.
• Company-provided software and necessary IT equipment for remote work.