Corva
Data Scientist, Completions Analytics
- Compensation
- Not disclosed
- Location
- Buenos Aires, Argentina
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Nice to have
- 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
Full description
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