Computational Data Science Researcher
Core
Develop and deploy advanced statistical, chemometric, and physics-informed AI models to convert complex chemical and process data into actionable insights for operational excellence and innovation in energy systems.
Role type
Senior individual contributor computational chemometrician and data science researcher
Builds
Scalable digital workflows for process monitoring, optimization, quality control, and R&D in Integrated Gas, Downstream, and Renewables & Energy Solutions
Domain
Energy sector (LNG, GTL, Renewables) + Chemometrics + Physics-informed Machine Learning
Deliverable
production ML models
Required skills
Chemometrics, Bayesian statistical learning, Physics- and chemistry-informed machine learning, Spectral and chromatographic modeling, Uncertainty quantification, Deterministic and stochastic optimization, Analytical chemistry techniques (chromatography, spectroscopy), Multivariate analysis, Time series analysis
Preferred skills
Reinforcement learning, GANs, Meta-learning, Active learning, Generative AI, Deep learning for spectroscopy, Manifold learning, Cloud-based scientific computing workflows
Technologies
Bayesian statistical learning frameworks, Spectral modeling tools, Chromatographic data analysis platforms, Cloud-based scientific computing environments
Responsibilities
Design and implement advanced chemometric and hybrid modeling frameworks; Define methodological strategy balancing interpretability and predictive performance; Collaborate with chemists and engineers to translate physicochemical behavior into computational solutions; Develop robust models for noisy, sparse datasets in real-time environments; Ensure model credibility through rigorous validation against experimental and operational data; Apply methods to identify variability drivers and support process optimization; Drive innovation in AI-enabled data analysis and contribute to scientific leadership via publications.
Seniority
Senior, hands-on IC with research leadership
