BS/MS in Engineering (Chemical) with minimum of 7 years prior experience
as AI/ML Specialist level role or BS/MS in any other background with
minimum of 5 years prior experience in Chemical Manufacturing
Knowledge and/or experience with data acquisition, preparation, and
validation.
Good knowledge and experience in handling large volume data sets using
...
Programming languages (python, SQL & other script languages) & various
ML models to develop predictive models to make operational improvement
decisions/business decisions.
Experience with cloud environments: data lake, data warehousing, Google
Cloud preferred.
strong experience in advanced analytics, model building, statistical modeling
Good knowledge and experience in handling implementing ML models (such
as regression models, Classification models, Clustering models, Deep
Learning Models)
Linear, Logistic Regression, Decision Trees, Random Forests, K-Nearest
Neighbours, Support Vector Machines.
Statistical techniques: ANOVA, Principal Component Analysis,
Deep Learning Methods: ANN, CNN, RNN, Transformers.
Good understanding and hands-on experience with time series and
forecasting modelling (ARIMA, SARIMA, Holt winter etc).
Good to have:
Statistical data analysis and Optimization Solvers (Gurobi, Cplex) and
Algebraic programming Languages (PulP).
Knowledge of Agile / Scrum is preferable.
Experience in deploying and monitor ML models in Operations, delivering
data products to end-users. Experience with ML CI/CD pipelines.
Develop an optimized solution from predictive models & convert them into
tool-based solution for operation/business team leaders.
Experience in Preventive maintenance predictive models, equipment
reliability analysis models are preferable but not mandatory.
show more
BS/MS in Engineering (Chemical) with minimum of 7 years prior experience
as AI/ML Specialist level role or BS/MS in any other background with
minimum of 5 years prior experience in Chemical Manufacturing
Knowledge and/or experience with data acquisition, preparation, and
validation.
Good knowledge and experience in handling large volume data sets using
Programming languages (python, SQL & other script languages) & various
ML models to develop predictive models to make operational improvement
decisions/business decisions.
Experience with cloud environments: data lake, data warehousing, Google
Cloud preferred.
strong experience in advanced analytics, model building, statistical modeling
Good knowledge and experience in handling implementing ML models (such
as regression models, Classification models, Clustering models, Deep
Learning Models)
Linear, Logistic Regression, Decision Trees, Random Forests, K-Nearest
Neighbours, Support Vector Machines.
Statistical techniques: ANOVA, Principal Component Analysis,
Deep Learning Methods: ANN, CNN, RNN, Transformers.
Good understanding and hands-on experience with time series and
...
forecasting modelling (ARIMA, SARIMA, Holt winter etc).
Good to have:
Statistical data analysis and Optimization Solvers (Gurobi, Cplex) and
Algebraic programming Languages (PulP).
Knowledge of Agile / Scrum is preferable.
Experience in deploying and monitor ML models in Operations, delivering
data products to end-users. Experience with ML CI/CD pipelines.
Develop an optimized solution from predictive models & convert them into
tool-based solution for operation/business team leaders.
Experience in Preventive maintenance predictive models, equipment
reliability analysis models are preferable but not mandatory.
show more