Data Scientist

You are a Data Scientist who bridges the worlds of advanced AI/ML and subsurface domain expertise. You possess strong Python capabilities combined with a deep understanding of Oil & Gas subsurface and wells challenges. Your passion lies in translating complex geoscience problems into elegant data science solutions that drive measurable business impact.

You thrive at the intersection of data science, subsurface domain knowledge, and digital platforms (including OSDU). You naturally build trust and collaborate with geoscientists, wells engineers, and data engineers, speaking both their technical language and yours.

Your Impact & Success Indicators Data Analysis & Insights

• Analyse large and complex datasets to identify trends, patterns, and insights
• Develop clear and actionable analyses to support business and operational decisions
• Perform exploratory data analysis (EDA) and statistical analysis
• Translate stakeholder questions into analytical approaches and outputs

Technical Excellence & Innovation You demonstrate mastery in developing and operationalizing AI/ML solutions that unlock subsurface value. You build production-grade models using Python, creating reusable pipelines that become organizational assets. Your statistical rigor and pattern recognition capabilities transform complex datasets into actionable intelligence.

Success looks like:

• Within 6 months: Deliver 2+ AI/ML models solving critical subsurface or wells challenges
• Within 12 months: Establish reusable ML frameworks reducing time-to-insight by 40%+
• Ongoing: Maintain model performance above agreed thresholds with clear explainability

Domain Value Creation You translate subsurface complexity into data science opportunity. Whether optimizing drilling operations, interpreting seismic features, predicting well log properties, or forecasting production, you understand the geological and engineering context behind the data. You speak the language of geoscientists and wells engineers, earning their trust through domain credibility.

Success looks like:

• Drive 3+ high-value use cases annually (seismic interpretation, drilling optimization, production forecasting)
• Influence critical subsurface decisions through model insights
• Become a trusted technical advisor to domain teams

Operational Excellence & MLOps You champion responsible AI and MLOps best practices, ensuring models are not just built but sustainably operated. You collaborate effectively with data engineers, establishing robust validation, monitoring, and governance processes. Your models are explainable, reproducible, and aligned with enterprise standards including OSDU.

Success looks like:

• Deploy models to production with full observability and monitoring
• Establish feedback loops ensuring continuous model improvement
• Contribute to organizational AI governance and standards

Collaboration & Enablement You multiply your impact through others, sharing knowledge, mentoring peers, and elevating the data science capability across teams. You communicate complex AI concepts clearly to non-technical stakeholders, building organizational AI literacy.

Success looks like:

• Enable 2+ team members to apply ML techniques independently
• Deliver insights that non-technical stakeholders can act upon confidently
• Contribute to shared codebases, documentation, and best practices, * Continuous learner: You stay current with evolving AI/ML techniques and industry trends
• Feedback seeker: You actively seek input from domain experts and stakeholders to improve models
• Responsible AI advocate: You champion ethical, explainable, and governed AI practices

Do you have a Master's degree?, Subsurface & Wells Domain Mastery You bring credible understanding of subsurface and wells workflows, having worked hands-on with:

• Seismic data (2D / 3D / 4D) and interpretation challenges
• Well logs, trajectories, and petrophysical analysis
• Drilling operations, completion design, and production surveillance

You understand the geological context behind the data, you know what anomalies matter, what patterns are geologically plausible, and how to validate models against domain knowledge. Geoscientists and engineers respect your technical depth and value your perspective., You are fluent in Python for data science and machine learning, with battle-tested experience across:

• Core libraries: NumPy, Pandas, SciPy for data manipulation and statistical analysis
• ML frameworks: scikit-learn for classical ML, TensorFlow and/or PyTorch for deep learning
• Techniques: time-series forecasting, classification, regression, clustering, and anomaly detection

You stay current with emerging AI capabilities (generative AI, foundation models) while maintaining pragmatism about when and how to apply them.

Enterprise Data Platforms You are comfortable working with large-scale data infrastructure:

• Data lakes and lakehouse architectures handling terabytes of subsurface data
• Cloud platforms (Azure and/or AWS) for compute, storage, and ML services
• Industry standards like OSDU for data integration and interoperability
• Modern ML tooling: notebooks, experiment tracking, model registries, and CI/CD pipelines

Professional Foundation

• Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Geoscience, Petroleum Engineering, or related field
• Typically 4-7+ years applying data science in complex technical domains
• Prior experience in Oil & Gas or subsurface-focused contexts strongly preferred

Who you are Mindset & Approach

• Intellectually curious: You ask "why" and "what if," constantly exploring new techniques while grounded in business value
• Pragmatic problem-solver: You balance theoretical elegance with practical impact, shipping solutions that work
• Domain learner: You invest time understanding the geology, physics, and engineering behind the data
• Value-driven: You measure success by business outcomes, not model accuracy alone
• Quality-focused: You take pride in robust, reproducible, explainable models

Collaboration Style

• Bridge builder: You connect technical and domain worlds, translating between data science and subsurface languages
• Team multiplier: You elevate others through knowledge sharing, mentoring, and collaborative problem-solving
• Clear communicator: You explain complex AI concepts to diverse audiences-from engineers to executives
• Trusted partner: You build credibility through delivery, transparency, and domain respect, * Experience with enterprise subsurface programs (Shell, major operators) or OSDU implementations
• Hands-on MLOps expertise: CI/CD for models, production deployment, monitoring at scale
• Advanced techniques: physics-informed ML, optimization, hybrid modelling combining data-driven and mechanistic approaches
• Leadership in responsible AI and model governance frameworks

At CGI, we combine challenging projects with excellent employment conditions:

• A permanent contract from the start
• A competitive salary aligned with your seniority
• 8% holiday allowance
• Bonus and profit-sharing scheme
• 20 statutory and 5 additional vacation days
• Lease budget / mobility budget
• NS Business Card
• Bicycle plan via CGI
• Option to invest in CGI shares
• Health insurance allowance of €116.35 gross per month
• €40 net work-from-home allowance per month
• A solid pension scheme
• Hybrid working