Expert, Data Scientist

United States, California, OaklandRequisition ID# 161233Job Category: Accounting / FinanceJob Level: Individual ContributorBusiness Unit: Operations - OtherWork Type: HybridJob Location: OaklandPosition SummaryThis position develops models to support aspects of the Vegetation Management Operational Analytics implementation and operations. This position designs, develops and executes scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes to develop and deploy models quantifying the probability of failure for vegetation in system territory. This individual collaborates with a multi-disciplinary project team of data scientists, data engineers, and subject matter experts on technical development phases: data engineering, analytics/modelling, and visualization/user interface. This individual interacts with technical and non-technical clients to resolve analysis and technical issues, working with teams, clients, and senior leadership throughout the development cycle practicing continuous improvement. This role aims to quantify vegetation risk and develop tools to enable risk-informed operational planning and decision making. This position is expected to drive down vegetation failures on the system to ensure the safety of our customers.Job Responsibilities:Shares and collaborates with other PG&E data science professionals.Works closely with domain experts to develop relevant domain knowledge in vegetation and electric assets, as well as knowledge of related datasets in climatology and meteorology.Maintains and enhances data pipelines within the Palantir Foundry platform.Works with business partners to advance business processes, based on analytical findings.Applies machine learning and first principles modeling methods to develop robust and reliable analytical models, including visualizations, within the Palantir Foundry & AWS SageMaker platforms.Documents data sources, methodology, and model evaluation metrics.Serves as the technical lead for development of high complexity models.Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.Works with sponsor departments and company subject matter experts to understand application and potential of modeling solutions that create value for end-users.Presents findings and makes recommendations to senior management.Works with all levels of leadership across functions to influence decisions.Works independently on highly complex issues. Applying advanced knowledge and problem-solving skills to wide-ranging issues. Integrates industry knowledge related to data into everyday business practices and decision making.QualificationsMinimum:Bachelor's degree in computer science, engineering, applied sciences, mathematics, statistics, econometrics or similar quantitatively focused subject areas or job-related experience.6+ years of relevant experience in data science or advanced analytics, OR master's degree and job-related experience, 6 years, OR Doctorate Degree and job-related experience, 3 years.Graduate degree in computer science, engineering, applied sciences, mathematics, statistics, econometrics or similar quantitatively focused subject areas or job-related experience.Relevant industry (vegetation, forestry) experience, 3 years.Experience collaborating on a data science team and conducting peer reviews of code and modeling work.Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.Experience with the following programming languages: PySpark, Python, and SQL.Experience with Palantir Foundry, AWS SageMaker, and GitHub.Ability to synthesize complex information into clear insights and translate those insights into decisions and actions.Ability to clearly communicate complex technical details and insights to colleagues and stakeholders.Familiarity with Agile product management.Detail-oriented and meticulous about documentation.

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