Data Scientist

Job Summary

This Data Scientist position is located in the Drilling department and is responsible for analyzing complex datasets to extract valuable insights, develop predictive models, and provide data-driven recommendations to enhance drilling performance. The Data Scientist works closely with cross-functional teams to support decision-making processes and drive continuous improvement in our operations. A significant focus will be on leveraging artificial intelligence (AI) and machine learning (ML) techniques to drive innovation and efficiency in drilling operations.

Duties and Responsibilities

• Collect, clean, and preprocess large datasets from various sources, including drilling sensors, logs, structured and unstructured databases.
• Develop and implement advanced analytical models, machine learning algorithms, and statistical techniques to identify trends, patterns, and anomalies in drilling data.
• Apply AI and ML techniques, including models such as XGBoost, Random Forest, and Neural Networks, to optimize drilling processes, predict equipment failures, and enhance safety measures.
• Collaborate with drilling engineers, geologists, and other stakeholders to understand their data needs and provide actionable insights.
• 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 to technical and non-technical audiences.
• Conduct root cause analysis of drilling issues and propose data-driven solutions to mitigate risks and improve performance.
• 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.
• Leverage Databricks for big data processing, analytics, and collaboration.
• Mentor and guide junior data scientists, providing technical expertise and support in their professional development.
• Document and present analytical methods, models, and results to ensure transparency and reproducibility.
• Other duties as assigned.

Skills and Competencies

• Strong proficiency in programming languages such as Python, R, and/or SQL.
• Knowledge of machine learning algorithms, statistical analysis, and predictive modeling techniques.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills to work effectively with cross-functional teams.
• Leadership skills and experience in managing projects and mentoring team members.
• Ability to work with large-scale datasets and perform complex data analysis.
• Proficiency in cloud computing platforms such as AWS.
• Experience with data engineering and ETL processes.
• Knowledge of geospatial analysis and GIS tools..

Required Qualifications

• Minimum four (4) years' experience within the Oil & Gas industry working as a Data Analyst, Engineering Tech, Engineering Specialist, Business Analyst, Systems Analyst, Systems Analyst, IT Analyst, or related role
• Technical proficiency in SQL, Python, or R.
• An acceptable pre-employment background and drug test

Preferred Qualifications

• Previous experience as a Drilling Engineer
• Bachelor's or Master's degree from an accredited college or university in Data Analytics, Computer Science, Information Science/Management, Mathematics, or related degree
• Experience with AI techniques such as natural language processing, computer vision, or deep learning
• Familiarity with drilling operations, geology, and reservoir engineering
• Experience with real-time data using WITSML and systems like Totco
• Experience with Databricks for big data processing and analytics
• Experience with advanced data tools like Alteryx Intelligence Suite and others.

Physical Requirements and Working Conditions

• Requires prolonged sitting, some bending, and stooping.
• Occasional lifting up to 25 pounds.
• Manual dexterity sufficient to operate a computer keyboard and calculator.

Continental Resources, Inc. provides equal employment and affirmative action opportunities to applicants and employees without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), age, sexual orientation, gender identity, national origin, protected veteran status, or disability.