Deskripsi pekerjaan Drilling Analytics Engineer PT Arka Data Pratama
About The Company
Arka Data is an Indonesian-based company that offers Drilling Intelligent Services solutions using data analytics, AI, and machine learning. We work closely with clients to provide customized solutions that enhance drilling efficiency, safety, productivity, and cost-effectiveness.
Qualification
To be qualified for this role, you should:
- Have a minimum of 1-2 years of professional experience as a Drilling Analytics Engineer with exposure to drilling operations, well planning, and performance monitoring.
- Hold a Bachelor’s degree in Petroleum Engineering, Earth Science, Information Technology, or a related discipline.
- Possess a strong understanding of drilling datasets (including Daily Drilling Reports and drilling parameters) and have experience in drilling performance analysis.
- Be proficient with data management and visualization tools such as advanced Excel functions, Power BI, or similar platforms.
- Demonstrate basic programming skills in Python, SQL, or equivalent tools to process and manage drilling data.
- Be able to translate operational drilling challenges into clear data and IT requirements for effective collaboration with drilling and IT teams.
Responsible
You will be responsible for:
- Collaborate with Drilling and IT teams to convert operational requirements into actionable data solutions.
- Developing, maintaining, and continuously improving drilling dashboards and digital tools using real-time and historical data to support operational decision-making.
- Supporting the development and enhancement of predictive models and machine learning applications to optimize drilling performance.
- Conducting performance analysis, including NPT, flat time, and efficiency metrics, and providing actionable insights to improve operations.
- Ensuring the quality, accuracy, and reliability of drilling data for analysis and reporting purposes.
Benefits:
- Opportunities for professional growth.
- Contribute to operational excellence in drilling through the application of analytics and digital initiatives.
- Professional development through predictive modeling, machine learning, and continuous improvement of drilling performance.