10 publicaciones de empleo destacadas de reliability engineer en lanús, buenos aires (¡Están contratando!)

Data Scientist, Completions Analytics
Corva —Buenos Aires, Buenos Aires
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Data Scientist, Completions Analytics

Corva -
Buenos Aires, Buenos Aires

Postulación rápida

Detalles del empleo

Tiempo completo
Hace 4 días

Descripción completa del empleo

About Corva

Corva 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.

Mission

Corva’s mission is to accelerate the future of energy.

Values

Boldness: 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 role

We are seeking a Senior Data Scientist to support the research, development, and deployment of
advanced 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 candidate
combines 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 transform
operational data into scalable tools, workflows, and decision-support applications that improve
efficiency, reliability, and performance across customer operations.

What you'll do

Analytics & Applied Research

Analyze large-scale operational datasets from completions, hydraulic fracturing, and production operations
Develop statistical, physics-based, empirical, and data-driven models to improve operational understanding and decision making
Conduct applied research focused on frac performance, pumping efficiency, equipment reliability, pressure analysis, and operational optimization
Design and execute studies to identify key drivers of operational performance
Develop algorithms and workflows for anomaly detection, forecasting, diagnostics, and optimization
Translate engineering problems into analytical solutions that provide measurable business value
Validate models and recommendations using field data and operational feedback
Software Development & Data Engineering
Design, develop, and maintain production-quality Python applications and analytics tools
Build scalable data processing pipelines for structured and time-series datasets
Develop reusable software components, libraries, and APIs supporting analytics workflows
Write clean, maintainable, and well-tested code following software engineering best practices
Participate in code reviews and contribute to shared codebases
Collaborate with software engineers to integrate analytical solutions into customer-facing products
Collaboration & Business Impact
Work closely with completions engineers, product managers, and software teams to define requirements and deliver solutions
Communicate analytical findings clearly to technical and non-technical stakeholders
Support customers and internal teams in understanding operational trends and performance drivers
Identify opportunities to improve operational efficiency, reduce costs, and increase asset performance
Document methodologies, assumptions, and analytical workflows

Qualifications
Education & Experience

Master's or PhD in Petroleum Engineering, Data Science, Statistics, Applied Mathematics, Engineering, Computer Science, or a related quantitative field
5+ years of experience in data science, analytics, engineering research, or software development
Experience working with oil and gas operational data
Strong preference for candidates with completions, hydraulic fracturing, stimulation, or production optimization experience
Experience delivering analytical solutions that drive measurable operational improvements
Technical Skills
Strong Python programming skills with experience developing production-quality software
Experience with scientific computing and data analysis libraries such as Pandas, NumPy, SciPy, and scikit-learn
Strong SQL and database experience
Experience working with time-series data and large operational datasets
Knowledge of statistical analysis, predictive modeling, and experimental design
Experience developing optimization, forecasting, or diagnostic workflows
Familiarity with software development best practices, version control, testing, and code reviews
Oil & Gas Domain Expertise
Strong understanding of hydraulic fracturing and completions operations
Knowledge of frac equipment, pumping operations, pressure analysis, treatment design, and operational KPIs
Experience analyzing frac, wireline, production, or well-performance datasets
Ability to identify operational anomalies, inefficiencies, and root causes from field data
Understanding of operational workflows and engineering decision-making processes
Preferred Qualifications
Experience with real-time operational data systems
Familiarity with cloud environments and data platforms
Experience with machine learning applications for forecasting, classification, or anomaly detection
Familiarity with geoscience, production, or reservoir engineering datasets
Experience publishing technical papers, patents, or industry presentations
Professional Skills
Strong analytical thinking and problem-solving abilities
Excellent written and verbal communication skills
Ability to work independently and manage multiple projects simultaneously
Effective collaboration within multidisciplinary teams
Ability to balance technical rigor with practical business needs
Strong organizational and documentation skills

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Data Scientist, Completions Analytics

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Senior Software Engineer (Java / Scala) - Argentina

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