Geology Data Analytics Scientist

Description

Position Summary

We are seeking a seasoned Data Analytics Scientist to drive the development and deployment of high-impact machine learning and analytics solutions across our energy operations. This role will focus on optimizing asset development strategies using geoscience, completions, drilling, and production data, while also building scalable BI pipelines and dashboards that empower smarter decision-making across the organization.  This position plays a pivotal role in bridging subsurface insights with surface operations, ensuring that data-driven strategies directly enhance well performance, cost efficiency, and field development planning.

Key Responsibilities 

• Lead the design, development, and deployment of advanced ML models to optimize exploration and completions strategies

• Architect and maintain cloud-native analytics pipelines using Python, SQL, and orchestration tools

• Build and enhance interactive dashboards using Tableau or Power BI with proactive insights via time-series forecasting, clustering, and regression

• Define and evolve BI strategy, identifying high-value analytics use cases across business units

• Collaborate with multidisciplinary teams to integrate solutions into operational workflows

• Apply spatial analytics and geostatistical methods to optimize well placement and reservoir characterization

• Integrate real-time sensor data (e.g., from SCADA systems) to support predictive maintenance and anomaly detection

• Support AFE (Authorization for Expenditure) modeling and capital allocation decisions through predictive analytics

• Contribute to ESG (Environmental, Social, Governance) reporting by analyzing emissions, water usage, and operational efficiency metrics

• Mentor data scientists and analysts through technical guidance, code reviews, and best-practice sharing

• Ensure high standards in code quality, version control, and documentation

• Present findings in clear, actionable formats for both technical and business audiences

• Other related duties as assigned.

Requirements

Qualifications

• 5 years applying ML and analytics in energy or E&P settings

• Proficiency in Python (Pandas, NumPy), SQL, and ML frameworks

• Experience with cloud platforms (AWS, GCP, Azure) and cloud data warehouses (e.g., BigQuery, AlloyDB, MSFT Fabric, )

• Hands-on experience with BI tools such as Tableau or Power BI.

• Advanced modeling and algorithm development for energy applications

• Deep understanding of upstream workflows including reservoir modeling, well planning, and hydraulic fracturing

• Experience working with oilfield data formats (e.g., LAS, WITSML, SEG-Y) and integrating with industry platforms like Petrel, Spotfire, or OSIsoft PI

• Knowledge of completions design parameters (e.g., proppant loading, stage spacing, fluid types) and their impact on production

• Familiarity with economic modeling tools and production forecasting software (e.g., Aries, PHDWin, Harmony)

• Ability to translate complex subsurface and operational data into actionable business insights

• Commitment to continuous innovation in ML/AI and energy technologies 

• Familiarity with regulatory and HSE (Health, Safety, Environment) data analytics

• Master’s in Data Science, Computer Science, Engineering, or related field (Bachelor’s with strong experience also considered)

• Strong cross-functional collaboration and stakeholder engagement

• Proven mentoring capabilities

• Strong communication skills and ability to manage multiple priorities

• High proficiency in Microsoft applications (such as Word, Excel, PowerPoint and Outlook).

• Excellent written and verbal communication skills.

• Excellent interpersonal skills including the ability to work as part of a team.

• Valid driver’s license.

Working Conditions and Physical Requirements

• Job is classified as light physical work in an office setting involving sitting, with intermittent periods of stooping, walking and standing.

• Occasionally may be required to lift, carry, push or pull 10-25 pounds.