Admin Ringan & Pembukuan | Invoice & Data Support (Tangerang)

Pt Hijau Abadi Lestari; Tangerang; A distancia; IDR 120.000.000 - 180.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work flexibility

Competitive salary package

Health benefits

Home office stipend

Professional development & online cert

Descripción de la vacante

Pt Hijau Abadi Lestari is seeking a Remote Data Analyst - Resource Management to join a global, fully remote team. You will analyze large mining datasets, build models, and create dashboards to drive operational insights and profitability.

Based in Indonesia with a flexible remote setup, you will collaborate with geologists, engineers, and management, applying Python, SQL, and visualization tools to deliver actionable intelligence and cost-saving opportunities across projects worldwide.

Formación

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Minimum of 5 years of experience in data analysis, with a focus on quantitative analysis and statistical modeling.
• Proven experience with data manipulation and analysis tools such as Python (Pandas, NumPy) or R.
• Proficiency in SQL for data extraction and manipulation.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Strong understanding of statistical concepts and machine learning algorithms.
• Excellent communication skills, with the ability to explain technical findings to non-technical audiences.
• Demonstrated ability to work independently and manage multiple priorities in a remote setting.
• Experience within the mining or natural resources sector is a significant plus.

Responsabilidades

• Collect, clean, and process large, complex datasets from mining operations.
• Develop and implement statistical models and machine learning algorithms to identify trends and anomalies.
• Create insightful data visualizations and dashboards using Tableau, Power BI, or similar.
• Analyze data related to resource exploration, ore grade, production output, and equipment performance.
• Collaborate with geologists, engineers, and management to understand data needs and provide analytical support.
• Identify opportunities for process improvements and cost reductions based on data analysis.
• Perform ad-hoc data analysis and generate reports to answer critical business questions.
• Ensure data integrity and accuracy across all analytical processes.
• Stay current with advancements in data analysis techniques, tools, and best practices.

Conocimientos

Data analysis

Python

SQL

Tableau

Power BI

Machine learning

Communication

Remote work

Educación

Bachelor's degree in Data Science or related field

Herramientas

Tableau

Power BI

SQL

Descripción del empleo

Remote Data Analyst - Resource Management

Our client is revolutionizing the mining industry through data-driven insights and is seeking a talented Remote Data Analyst to join their expanding global team. This fully remote position, based out of Pekanbaru, Riau, ID (conceptually, as the role is remote), will focus on analyzing vast datasets related to mineral resources, extraction efficiency, and operational performance. You will be instrumental in transforming raw data into actionable intelligence that guides strategic decision-making and enhances operational profitability. The ideal candidate is a self-starter, possesses exceptional analytical skills, and thrives in a distributed work environment. This is a fantastic opportunity to leverage your expertise in data science and contribute to the future of responsible mining operations from anywhere in the world.

Key Responsibilities

• Collect, clean, and process large, complex datasets from various mining operations.
• Develop and implement statistical models and machine learning algorithms to identify trends, patterns, and anomalies in mining data.
• Create insightful data visualizations and dashboards using tools like Tableau, Power BI, or similar.
• Analyze data related to resource exploration, ore grade, production output, equipment performance, and environmental impact.
• Collaborate with geologists, engineers, and management teams to understand their data needs and provide analytical support.
• Identify opportunities for process improvements and cost reductions based on data analysis.
• Perform ad-hoc data analysis and generate reports to answer critical business questions.
• Ensure data integrity and accuracy across all analytical processes.
• Stay current with advancements in data analysis techniques, tools, and best practices in the mining sector.

Requirements

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Minimum of 5 years of experience in data analysis, with a focus on quantitative analysis and statistical modeling.
• Proven experience with data manipulation and analysis tools such as Python (Pandas, NumPy) or R.
• Proficiency in SQL for data extraction and manipulation.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Strong understanding of statistical concepts and machine learning algorithms.
• Excellent communication skills, with the ability to explain technical findings to non-technical audiences.
• Demonstrated ability to work independently and manage multiple priorities in a remote setting.
• Experience within the mining or natural resources sector is a significant plus.

Benefits

As a fully remote employee, you will benefit from unparalleled flexibility and work-life balance. Our client provides a competitive salary package, comprehensive health benefits, and opportunities for professional development and online certifications. You will have access to the latest analytical software and cloud computing resources. A home office stipend is provided to ensure a productive work environment. Opportunities for advancement to senior analyst or data science lead roles are available for high-performing individuals. Join a forward-thinking company that embraces remote work and values the contributions of its distributed talent pool.