Computational Data Science Researcher

About the Role

The Computational Chemometrician is a technical contributor and subject-matter expert who applies advanced analytics and modeling techniques to extract value from high-dimensional datasets, including chemical, physical, and process data.

Operating at the interface of mathematics, statistics, engineering, chemistry, and digital technologies, the role supports improved understanding, optimization, and control of complex industrial and energy systems.

Key Responsibilities

• Design, develop, and implement advanced chemometric and hybrid modeling frameworks for chemical and process systems.
• Define and guide methodological strategy by selecting appropriate modeling approaches, ranging from classical chemometrics and statistics to modern AI and mechanistic models.
• Collaborate closely with chemists, process engineers, and domain experts to translate physicochemical behavior, operating regimes, and sources of variability into structured analytical problems and computational solutions.
• Develop robust, scalable, and deployable models capable of handling noisy, sparse, and biased datasets.
• Ensure model credibility through rigorous validation against experimental, simulated, and operational data.
• Apply chemometric and statistical methods to enhance process understanding by identifying drivers of variability, detecting anomalies, and performing root-cause analysis.
• Drive innovation in AI-enabled data analysis by exploring and applying advanced techniques such as deep learning for spectroscopy and manifold learning.

Skills & Qualifications

• PhD in Applied Statistics, Data Science, Chemometrics, Mathematics, and/or Engineering.
• Experience in large-scale parameterization and process data modeling and optimization.
• Strong AI expertise and hands-on experience in advanced areas such as reinforcement learning, GANs, meta-learning, active learning, and generative AI.
• Proven experience in deterministic and stochastic optimization.
• Knowledge of design of experiments, general linear modeling, multivariate analysis, statistical modeling, and/or time series analysis.
• Demonstrated strong problem-solving skills, with the ability to work both independently and collaboratively within a team environment.
• Excellent communication skills, with a proven ability to clearly convey complex technical concepts to diverse audiences.

What You'll Learn

In this role, you will develop the skills you need to grow in an environment where we value honesty, integrity, and respect for one another.

You'll have the opportunity to work with talented, committed people on one of the most important challenges facing our planet.

Progress as a person as we work on the energy transition together.

Resume Tip

When applying for this role, be sure to highlight your experience in large-scale parameterization and process data modeling and optimization, as well as your knowledge of advanced AI techniques such as reinforcement learning and GANs.

Also, be sure to emphasize your ability to work collaboratively within a team environment and your excellent communication skills.

This will help you stand out as a strong candidate and increase your chances of getting an interview.