Expert Data Engineer

Wildfire Data ScientistRequired Skills & Experience:Professional experience with large data sets; strong on managing and querying large amount of data sets (foundry is a plus), having the ability to be able to query effectively or subset effectively a large set of data, petitioning, shuffling, all the techniques out thereProficiency in Python and ML Frameworks like Tensor Flow or PyTorchPractical experience with cloud infrastructure AWS Sagemaker (s3, Lambda, Glue) and/or Snowflake and Palantir FoundryExperience with containerization and container orchestration tools like Docker, Kubernetes, Experience with Docker to create reproducible environments for data processing and model deploymentProficiency with software engineering best practices: version control, testing and CI/CD automation (e.g., GitHub, Jenkins)Experience implementing model versioning, deployment, monitoring and observability systemsExperience with Remote Sensing data and geospatial technologies(Nice to Have)Experience with deep learning at scale with geospatial remote sensing dataAbility to manage the end-to-end ML lifecycle across platforms (e.g. Palantir Foundry and AWS SageMaker) Utilities experience or experience with environmental data GIS/GeospatialJob Description:The aim of the Wildfire Data Science team in the Wildfire Risk Management organization is to enhance the risk practices of PG&E's Electric Operation business and thereby address changing external conditions such as climate change. To this end the Wildfire Data Science team develops and maintains predictive models to enable PG&E to close the gap between metrics and electric system performance.

These models provide a multi-layered view of risk and risk reduction across the electric system so that decision-making processes include and empower employees at all levels of the company to manage risk appropriately.Sample activities include:Quantification of wildfire mitigation program performance on the distribution and transmission electric system.Development of causal inference models using PySpark and executed in Foundry or AWS.Interpretation and representation of meteorological data in models that combine a range of data sources such as the electric system asset data, vegetation, and meteorology.Position Summary:Designs, develops, and executes scripts, programs, models, algorithms, and processes, using structured and unstructured data from disparate sources and sizes, generating for defensible, valid, scalable, reproducible and documented machine learning and artificial intelligence models (predictive or optimization) for problem solving and strategy development. Participates in internal and external communities of practice in data science/artificial intelligence/machine learning to advance knowledge in the field. Educates the non-technical community on advantages, risks, and maturity levels of data science solutions.Job Responsibilities:Researches 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 setsExtracts, transforms, and loads data from dissimilar sources from across PG&E for their machine learning feature engineeringApplies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible predictive or optimization models that involve multiple facets and iterations in algorithm development.Wrangles and prepares data as input of machine learning model development and feature engineeringArchitects, 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 processes, and advanced data analysis.Works with stakeholder departments and company subject matter experts to understand application and potential of data science solutions that create value.Presents findings and makes recommendations to senior management.Act as peer reviewer of complex models