Senior Scientist, Chemical Engineering
Our client is searching for a scientist to join the team and help save the world. The right candidate will have experience in the chemical, electrochemical or petrochemical process industry and a keen interest in removing carbon from the air. Reporting to the Manager, Plant Operations, you will spearhead the implementation of robust experiment design and data analysis methods as well as identifying and exploiting process optimization opportunities across the company’s Direct Air Capture and Fuel Synthesis technologies. The successful candidate will have an opportunity to shape this new role, support the company in becoming a data-driven organization and champion best practices in experiment design.
Implement experiment design and data analysis methods to optimize the output of test campaigns.
Identify and exploit opportunities for Pilot Plant process optimization.
Act as a chemical process Subject Matter Expert within the operations team.
Act as senior process advisor to the Manager, Plant Operations.
Identify meaningful Pilot Plant KPIs to characterize and validate plant performance and set control limits.
Identify and assess opportunities for commercial plant CAPEX/OPEX reduction through Pilot Plant KPI optimization.
Create and communicate best practices and mentor operations team staff in all aspects of experiment design and statistical data analysis to ensure that test campaigns maximize learning opportunities.
Advise process leads on data gathering requirements for effective process/relationship characterization.
Develop data management functionality that enhances data output in order to maximize characterization opportunities.
Participate as a team member in experiment design, planning and review meetings.
Perform probabilistic and deterministic linkages of data output.
Education: PhD in Chemical Engineering or Chemistry with substantial research experience.
Experience: 8+ years of relevant process development and characterization experience.
Hands-on experience and comfort working in a development environment.
Proficiency in analyzing data using statistical methods (e.g. regression modelling, time series analysis, inference, Bayesian methods, sampling theory, decision theory, likelihood estimation).
Strong understanding of experiment design (e.g. multivariate testing, full factorial, fractional-factorial).
Experience using statistical analysis packages such as Minitab or R.
Experience analyzing and deriving insights from large datasets (10M+ data points/day) is a bonus.
Ability to balance multiple demands and work both independently and as part of a team.
Creative analytical and problem-solving skills with strong attention to detail.
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