I'm looking for an experienced data scientist who has had some experience working on process optimisation (engineering related) problems. My data set is from a power plant desulphurisation process which has approx. 100,000 observations and 30 variables. Using this data set, I would like to model the number pumps used in the process with respect to the other variables. Then based on the derived model, you would need to find the optimal solution at which the number of pumps used is minimised subject to a few inequality constraints. This is an interesting problem and I'm confident that whoever takes on this challenge will find it rewarding! I would need the code written in R. Also, practical experience in Machine Learning and Nonlinear Programming would be required. If selected for an interview, further details about the project/expectation will be provided. I look forward to receiving your application.