Data Science

Job Description:

Data Science

Position : Data Science Duration : 12 months Location : San Francisco, CA   Remote Work Permitted: Due to COVID-19, the client has agreed to allow the selected candidate to work remotely for the time being. 

Position:Data Science

Responsibilities:

Develop, maintain, and improve computer vision models which are hosted on AWS for scaled use Evaluate the performance of various Convolutional Neural Network (CNN) architectures and communicate the results to the business to demonstrate the value created through the deployment of such models Appropriately document data sources, methodology, and evaluation metrics through using visual tools Understand apply statistical techniques, analytical methods, and machine learning models such as classification, regression, clustering, anomaly detection, and neural networks to identify opportunities for operational improvement and develop strategic insight Work closely with domain experts and develop a working knowledge of rate structures and elements, load shapes, and distributed energy resource technologies and policy options Work with the leadership to continually improve analytics via demonstrations, mentoring, and disseminating best practices Required Qualifications:

Bachelor s Degree in Computer Science, Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics or job-related discipline or equivalent experience Job-related experience (e.g. data analytics and modeling), 5 years, OR Masters Degree and job-related experience, 3 years, OR Doctorate Additional Qualifications:

Track record of writing clear and well documented code preferably in Python Experience developing supervised and unsupervised learning models, neural networks (CNN, RNN, GCN, etc.) Familiarity with deep learning frameworks (PyTorch, TensorFlow) Excellent oral and written communication skills Enjoy working on complex multi-stage projects with a diverse team Involvement or strong interest in the energy industry Expressed interest in learning, experimentation, and incorporation of new techniques Distributed and cloud computing experience Experience working with large datasets and knowledgeable about parallelization Familiarity with transmission and distribution power flow models