Data Scientist

Job Title: Data Scientist

Position Summary

The Chord Energy Data Scientist role is a technical individual contributor role, focused on supporting business opportunities through the use of exploratory data analytics, machine learning models and generative AI opportunities. This position is located in Downtown Houston, TX. Hybrid work schedule is an option for remote work on Mondays and Fridays. Level and salary commensurate with experience.

Essential Job Functions

The primary responsibility involves leading and participating in multi-disciplinary projects aimed at providing business solutions to a diverse set of problems ranging from, but not limited to, production automation/optimization, drilling and completion process optimization, back-office process improvement and automation, dashboard generation and deployment, and computer vision aided operations. Additionally, the Data Scientist will contribute to the adoption of new technologies and best practices for analytical workflows. The ability to work well in a team and in support of core business functions will be critical to the success of this role.   

This job description is not intended to be an all-inclusive list of duties and responsibilities of the position. Incumbents will be required to follow any other job-related instructions and duties outside of their normal responsibilities as assigned by their supervisor.

Minimum Qualifications

• Master's or Bachelor's degree in Data Science, Computer Science, or related field
• 5+ years in data science/ML (including time-series, geospatial, and predictive modeling)
• Proven experience and/or education in data analytics and management of large datasets
• Proficiency in Python (pandas, scikit-learn) and SQL; experience with Azure ML/MLflow and deploying models to production.
• Domain familiarity with upstream oil & gas workflows (subsurface and operations) and the ability to translate expert knowledge into features and experiments.
• Strong interpersonal and collaborative skills
• Demonstrated ability to work in a team-oriented environment
• Excellent presentation skills
• Ability to work in a fast-paced and fluid environment; flexible with the demands of a growing company
• Strong coaching, prioritization, and stakeholder-management skills; able to convert business problems into robust, scalable model solutions and communicate outcomes clearly.
• Ability to meet deadlines
• Physical Requirements and Working Conditions: Must possess mobility to work in a standard office setting and to use standard office equipment, including a computer, stamina to maintain attention to detail despite interruptions, strength to lift and carry files weighing up to 10 pounds; vision to read printed materials and a computer screen, and hearing and speech to communicate in person and over the telephone

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Preferred Qualifications

• Master’s degree or PHD or certification in Data Science or Data Analytics
• Familiarity with additional programming languages (SQL, R, C++, etc.)
• Previous Oil and Gas operator experience
• Exposure to Petroleum Engineering and Geoscience workflows
• Exposure to the energy sector, particularly unconventional exploitation programs

This role presents an exciting opportunity for a data scientist to contribute to the advancement of Chord's data science transformation, leveraging expertise in data analytics to drive innovation and optimize operational outcomes.

EEO Statement:

Chord Energy does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.