Data Scientist - Drilling Department

Position Overview

• Location Type: Onsite
• Job Type: Full time
• Salary: Not specified

A Data Scientist position within the Drilling department is responsible for analyzing complex datasets to extract valuable insights, develop predictive models, and provide data-driven recommendations to enhance drilling performance. This role will leverage AI and machine learning techniques to drive innovation and efficiency in drilling operations, working closely with cross-functional teams to support decision-making.

Responsibilities

• Data Collection & Processing: Collect, clean, and preprocess large datasets from various sources, including drilling sensors, logs, structured and unstructured databases.
• Model Development: Develop and implement advanced analytical models, machine learning algorithms, and statistical techniques to identify trends, patterns, and anomalies in drilling data.
• AI/ML Implementation: Apply AI and ML techniques (e.g., XGBoost, Random Forest, Neural Networks) to optimize drilling processes, predict equipment failures, and enhance safety measures.
• Collaboration: Collaborate with drilling engineers, geologists, and other stakeholders to understand their data needs and provide actionable insights.
• Data Visualization: Design and build data visualizations and dashboards using tools such as Python charts (e.g., Matplotlib, Seaborn) and JavaScript charts (e.g., D3.js, Chart.js) to effectively communicate findings.
• Root Cause Analysis: Conduct root cause analysis of drilling issues and propose data-driven solutions to mitigate risks and improve performance.
• Real-time Data Integration: Work with real-time data using WITSML (Wellsite Information Transfer Standard Markup Language) and systems like Totco to enhance real-time monitoring and decision-making.
• Big Data Processing: Leverage Databricks for big data processing, analytics, and collaboration.
• Mentorship: Mentor and guide junior data scientists, providing technical expertise and support.
• Documentation & Presentation: Document and present analytical methods, models, and results to ensure transparency and reproducibility.
• Other Duties: Perform other duties as assigned.

Requirements

• Programming Skills: Strong proficiency in programming languages such as Python, R, and/or SQL.
• Machine Learning Knowledge: Knowledge of machine learning algorithms, statistical analysis, and predictive modeling techniques.
• Problem-Solving: Excellent problem-solving skills and attention to detail.
• Communication & Collaboration: Strong communication and collaboration skills to work effectively with cross-functional teams.
• Leadership (Desired): Leadership skills and experience in managing projects and mentoring team members.
• Data Handling: Ability to work with large-scale datasets and perform complex data analysis.
• Cloud Computing: Proficiency in cloud computing platforms such as AWS.
• Data Engineering: Experience with data engineering and ETL processes.
• Geospatial Analysis: Knowledge of geospatial analysis and GIS tools.

Application Instructions

• Not specified

Company Information

• Not specified (Oil & Gas Industry - Drilling Department)