Principal Data Scientist

Job TitlePay Range: $128.66hr - $148.45hrRequirement/Must HaveMaster’s Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field.Experience in Data Science, 8+ years or 2+ years experience if possessing Doctoral Degree or higher in a related field.ResponsibilitiesResearches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.Creates advanced data mining architectures/models/ protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets.Extracts, transforms, and loads data from dissimilar sources for machine learning feature engineering.Applies data science/machine learning/artificial intelligence methods to develop defensible and reproducible predictive or optimization models.Wrangles and prepares data as input for machine learning model development and feature engineering.Architects, develops, and documents reusable functions and modular code for data science.Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures, and advanced data analysis.Works with stakeholder departments and subject matter experts to understand application and potential of data science solutions.Presents findings and makes recommendations to senior management.Acts as peer reviewer of complex models.Nice to HaveDoctorate Degree in Data Science, Machine Learning, Computer Science, Civil Engineering, Mechanical Engineering, Electrical Engineering, Statistics, or equivalent field.Expertise in experimental design and causal inference methods.Expertise in statistical methods for time series analysis, statistical modeling, and probabilistic risk assessment.Relevant industry experience (electric or gas utility, data science consulting, etc.).Familiarity with the use of supervised, unsupervised, deep learning & physics-based methods for modeling electrical infrastructure failure modes.Competency with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices.Knowledge of industry trends and current issues in job-related area of responsibility.Competency with Agile product development best practices.Proficiency with Python or PySpark, code reviews, and code development best practices.Proficiency in explaining technical concepts including statistical inference, machine learning algorithms, software engineering, model deployment pipelines.Mastery in clearly communicating complex technical details and insights to colleagues and stakeholders.Ability to develop, coach, teach and/or mentor others to meet both their career goals and the organization goals.SkillsPyspark proficiency.User interface development proficiency.Strong cross-functional collaboration skills.