We're excited to introduce an exceptional data scientist with expertise in machine learning and data science, particularly in the climate tech space. This candidate possesses extensive experience developing statistical and machine learning models for time series classification problems using various types of data. Their technical skill set includes programming languages such as Python, SQL, Pandas, NumPy, scikit-learn, Tensorflow, and AWS ECS, along with knowledge and experience in Bayesian statistics and unsupervised learning. Moreover, they have demonstrated an ability to manage technical debt while still working towards scalable model deployment and feature adoption.
In terms of education, this candidate holds an MS in Computer Science with a Machine Learning Specialization and a BS in Mathematics & Physics. During their undergraduate studies, they won an award and published a paper on "Sustainable Greywater Filtration on a Residential Scale."
Overall, this candidate is an excellent fit for any company looking for a data scientist with a passion for making a positive environmental impact. With their technical skills and expertise, they can provide unique solutions to help meet specific client needs such as reducing energy consumption and greenhouse gas emissions. Their experience in developing Bayesian and deep learning models for time series classification problems using various types of data and HPC resources can be leveraged to deliver scalable model deployment and feature adoption.
Machine Learning, Statistical Modeling, Programming, Data Analysis, Bayesian Statistics