{"id":76799,"url":"https://alion.io/job/corva-data-scientist-completions-analytics","title":"Data Scientist, Completions Analytics","company":{"id":23615,"name":"Corva","domain":"corva.ai","url":"https://alion.io/company/corva","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":{"grade":"C","score":56,"open_postings":15,"ghost_share":0.733,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Buenos Aires, Argentina"],"countries":["AR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":42000,"max_usd":109000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2324},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SciPy","optional":false},{"name":"SQL","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-06-01T16:52:14Z","employer_posted_date":"2026-06-01","last_verified_at":"2026-10-18T05:59:20Z","board_verified":true,"closed_at":null,"days_open":138,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":138},"description":"About Corva\nCorva 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.\nCorva is powering worldwide innovation by driving efficiency, productivity, and profitability with our innovative energy solutions.\nMission\nCorva’s mission is to accelerate the future of energy.\nValues\nBoldness: Corvanauts have the confidence and courage to question status quo for the products we make and the relationships we cultivate.\nOwn End-to-End: We take ownership of what we start and see it through to completion through trust and dependability.\nTransparency: 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.\nBias 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.\n About the role\nWe are seeking a Senior Data Scientist to support the research, development, and deployment of\nadvanced analytics solutions for hydraulic fracturing, completions, and production operations.\nThis role focuses on applying data analysis, statistical modeling, physics-informed approaches,\nand software development to solve complex operational challenges. The ideal candidate\ncombines strong Python programming skills with a deep understanding of oilfield operations,\nparticularly completions and hydraulic fracturing.\nYou will work closely with engineers, domain experts, and software developers to transform\noperational data into scalable tools, workflows, and decision-support applications that improve\nefficiency, reliability, and performance across customer operations.\nWhat you'll do\nAnalytics & Applied Research\nAnalyze large-scale operational datasets from completions, hydraulic fracturing, and production operations\nDevelop statistical, physics-based, empirical, and data-driven models to improve operational understanding and decision making\nConduct applied research focused on frac performance, pumping efficiency, equipment reliability, pressure analysis, and operational optimization\nDesign and execute studies to identify key drivers of operational performance\nDevelop algorithms and workflows for anomaly detection, forecasting, diagnostics, and optimization\nTranslate engineering problems into analytical solutions that provide measurable business value\nValidate models and recommendations using field data and operational feedback\nSoftware Development & Data Engineering\nDesign, develop, and maintain production-quality Python applications and analytics tools\nBuild scalable data processing pipelines for structured and time-series datasets\nDevelop reusable software components, libraries, and APIs supporting analytics workflows\nWrite clean, maintainable, and well-tested code following software engineering best practices\nParticipate in code reviews and contribute to shared codebases\nCollaborate with software engineers to integrate analytical solutions into customer-facing products\nCollaboration & Business Impact\nWork closely with completions engineers, product managers, and software teams to define requirements and deliver solutions\nCommunicate analytical findings clearly to technical and non-technical stakeholders\nSupport customers and internal teams in understanding operational trends and performance drivers\nIdentify opportunities to improve operational efficiency, reduce costs, and increase asset performance\nDocument methodologies, assumptions, and analytical workflows\nQualifications\nEducation & Experience\nMaster's or PhD in Petroleum Engineering, Data Science, Statistics, Applied Mathematics, Engineering, Computer Science, or a related quantitative field\n5+ years of experience in data science, analytics, engineering research, or software development\nExperience working with oil and gas operational data\nStrong preference for candidates with completions, hydraulic fracturing, stimulation, or production optimization experience\nExperience delivering analytical solutions that drive measurable operational improvements\nTechnical Skills\nStrong Python programming skills with experience developing production-quality software\nExperience with scientific computing and data analysis libraries such as Pandas, NumPy, SciPy, and scikit-learn\nStrong SQL and database experience\nExperience working with time-series data and large operational datasets\nKnowledge of statistical analysis, predictive modeling, and experimental design\nExperience developing optimization, forecasting, or diagnostic workflows\nFamiliarity with software development best practices, version control, testing, and code reviews\nOil & Gas Domain Expertise\nStrong understanding of hydraulic fracturing and completions operations\nKnowledge of frac equipment, pumping operations, pressure analysis, treatment design, and operational KPIs\nExperience analyzing frac, wireline, production, or well-performance datasets\nAbility to identify operational anomalies, inefficiencies, and root causes from field data\nUnderstanding of operational workflows and engineering decision-making processes\nPreferred Qualifications\nExperience with real-time operational data systems\nFamiliarity with cloud environments and data platforms\nExperience with machine learning applications for forecasting, classification, or anomaly detection\nFamiliarity with geoscience, production, or reservoir engineering datasets\nExperience publishing technical papers, patents, or industry presentations\nProfessional Skills\nStrong analytical thinking and problem-solving abilities\nExcellent written and verbal communication skills\nAbility to work independently and manage multiple projects simultaneously\nEffective collaboration within multidisciplinary teams\nAbility to balance technical rigor with practical business needs\nStrong organizational and documentation 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