Data Scientist, Completions Analytics

About CorvaCorva has built a first-of-its-kind energy app store on a bedrock of best-in-class technologies, data pipelines, and a secure and scalable architecture. Our energy solutions solve today's toughest well delivery challenges, from well design through drillout. The ever-evolving platform is not only future-proof for digitizing operations but is your toolkit to accelerate sustainability and energy transition goals. Our platform is built for speed and reliability and delivers unmatched features and capabilities.Corva is powering worldwide innovation by driving efficiency, productivity, and profitability with our innovative energy solutions.MissionCorva’s mission is to accelerate the future of energy.ValuesBoldness: Corvanauts have the confidence and courage to question status quo for the products we make and the relationships we cultivate.Own End-to-End: We take ownership of what we start and see it through to completion through trust and dependability.Transparency: It's crucial to be open and honest and consistent with updates and data flow with customers and colleagues. We value the free-flowing of information and data to make better decisions.Bias Action: Corvanauts don't sit still - our default mode is taking action! We make progress through high-quality iterations. Failure is built into the process and success is defined by the number of shots on goal.About the roleWe are seeking a Senior Data Scientist to support the research, development, and deployment ofadvanced analytics solutions for hydraulic fracturing, completions, and production operations.This role focuses on applying data analysis, statistical modeling, physics-informed approaches,and software development to solve complex operational challenges. The ideal candidatecombines strong Python programming skills with a deep understanding of oilfield operations,particularly completions and hydraulic fracturing.You will work closely with engineers, domain experts, and software developers to transformoperational data into scalable tools, workflows, and decision-support applications that improveefficiency, reliability, and performance across customer operations.What you'll doAnalytics & Applied ResearchAnalyze large-scale operational datasets from completions, hydraulic fracturing, and production operationsDevelop statistical, physics-based, empirical, and data-driven models to improve operational understanding and decision makingConduct applied research focused on frac performance, pumping efficiency, equipment reliability, pressure analysis, and operational optimizationDesign and execute studies to identify key drivers of operational performanceDevelop algorithms and workflows for anomaly detection, forecasting, diagnostics, and optimizationTranslate engineering problems into analytical solutions that provide measurable business valueValidate models and recommendations using field data and operational feedbackSoftware Development & Data EngineeringDesign, develop, and maintain production-quality Python applications and analytics toolsBuild scalable data processing pipelines for structured and time-series datasetsDevelop reusable software components, libraries, and APIs supporting analytics workflowsWrite clean, maintainable, and well-tested code following software engineering best practicesParticipate in code reviews and contribute to shared codebasesCollaborate with software engineers to integrate analytical solutions into customer-facing productsCollaboration & Business ImpactWork closely with completions engineers, product managers, and software teams to define requirements and deliver solutionsCommunicate analytical findings clearly to technical and non-technical stakeholdersSupport customers and internal teams in understanding operational trends and performance driversIdentify opportunities to improve operational efficiency, reduce costs, and increase asset performanceDocument methodologies, assumptions, and analytical workflowsQualifications Education & ExperienceMaster's or PhD in Petroleum Engineering, Data Science, Statistics, Applied Mathematics, Engineering, Computer Science, or a related quantitative field5+ years of experience in data science, analytics, engineering research, or software developmentExperience working with oil and gas operational dataStrong preference for candidates with completions, hydraulic fracturing, stimulation, or production optimization experienceExperience delivering analytical solutions that drive measurable operational improvementsTechnical SkillsStrong Python programming skills with experience developing production-quality softwareExperience with scientific computing and data analysis libraries such as Pandas, NumPy, SciPy, and scikit-learnStrong SQL and database experienceExperience working with time-series data and large operational datasetsKnowledge of statistical analysis, predictive modeling, and experimental designExperience developing optimization, forecasting, or diagnostic workflowsFamiliarit