Electricenergyonline
Data Scientist Pacific Gas and Electric Company Location: California Category: D
Electricenergyonline, Oakland, California, United States, 94616
Position Summary
PG&E is looking for a Data Scientist with experience in data science products and ML DevOps. In this role, the successful candidates will play a vital role in building and maintaining the infrastructure that brings our machine learning models to life, having the opportunity to advance PG&E's triple bottom line of People, Planet, and Prosperity. Working as part of cross-functional teams, including data scientists, ML engineers, and software engineers to ensure seamless integration and deployment of models into the production environment. The responsibilities of these positions include:As a Center of Excellence team member in the centralized data science Hub, support analytics Spokes across the company in the implementation of the ML DevOps Framework for their productionalized models.Assist in developing and documenting the standards ML DevOps pipelines for training, testing, deployment, and monitoring of machine learning models.Collaborate with data scientists and ML engineers to understand model requirements and translate them into production-ready pipelines.Participate in the design and implementation of CI/CD pipelines for machine learning models.Participate in code reviews and contribute to the improvement of existing ML DevOps tools.Monitor model performance in production and identify potential issues.Assist in troubleshooting and resolving issues related to model deployments.Stay up to date on the latest ML DevOps trends and technologies.Participate in the design, development, and testing of ML DevOps pipelines.Write and maintain well-documented, efficient, and scalable ML DevOps code.Build and maintain strong relationships with business units and external agencies.A reasonable salary range is:Bay Area: $102,000.00 - $162,000.00California: $97,000.00 - $154,000.00This position is hybrid, working from your remote office and your assigned work location based on business need. The assigned work location will be within the PG&E Service Territory.Reporting RelationshipThis position reports to the Director, Enterprise Decision Science/Data Science & Analytics Products.Job Responsibilities:Develop and document the standards ML DevOps pipelines for training, testing, deployment, and monitoring of machine learning models.Extract, transform, and load data from dissimilar sources from across PG&E for their machine learning feature engineering.Support the application of data science/machine learning/artificial intelligence methods to develop defensible and reproducible predictive or optimization models.Support and implement the ML model governance and monitoring of model performance in production.Support the development of mathematical models and AI simulations which represent complex business problems.Write and document python code for data science (feature engineering and machine learning modeling), and ML DevOps under senior data scientist guidance.Contribute to the development of summary presentations.Communicate technical information clearly to other data scientists.Qualifications :Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field2 years in data science (or no experience, if possess Master's Degree)Desired:Master's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent fieldRelevant industry experience (electric or gas utility, renewable energy, analytics consulting, etc.)Knowledge, Skills, Abilities and (Technical) CompetenciesFamiliarity with data science and ML DevOps standards and processes (model evaluation, optimization, feature engineering, model deployment, monitoring, etc.) along with best practices to implement them.Knowledge of software engineering, statistics, and machine learning techniques as they apply to data science modeling and deployment.Knowledge of commonly used data science and/or operations research programming languages, packages, and tools.Hands-on knowledge and application of data science/machine learning models and algorithms.Ability to clearly communicate complex technical details and insights to colleagues and stakeholders.Knowledge of the mathematical and statistical fields that underpin data science.Knowledge of systems thinking and structuring complex problems.Ability to collaborate and/or work on a team.
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PG&E is looking for a Data Scientist with experience in data science products and ML DevOps. In this role, the successful candidates will play a vital role in building and maintaining the infrastructure that brings our machine learning models to life, having the opportunity to advance PG&E's triple bottom line of People, Planet, and Prosperity. Working as part of cross-functional teams, including data scientists, ML engineers, and software engineers to ensure seamless integration and deployment of models into the production environment. The responsibilities of these positions include:As a Center of Excellence team member in the centralized data science Hub, support analytics Spokes across the company in the implementation of the ML DevOps Framework for their productionalized models.Assist in developing and documenting the standards ML DevOps pipelines for training, testing, deployment, and monitoring of machine learning models.Collaborate with data scientists and ML engineers to understand model requirements and translate them into production-ready pipelines.Participate in the design and implementation of CI/CD pipelines for machine learning models.Participate in code reviews and contribute to the improvement of existing ML DevOps tools.Monitor model performance in production and identify potential issues.Assist in troubleshooting and resolving issues related to model deployments.Stay up to date on the latest ML DevOps trends and technologies.Participate in the design, development, and testing of ML DevOps pipelines.Write and maintain well-documented, efficient, and scalable ML DevOps code.Build and maintain strong relationships with business units and external agencies.A reasonable salary range is:Bay Area: $102,000.00 - $162,000.00California: $97,000.00 - $154,000.00This position is hybrid, working from your remote office and your assigned work location based on business need. The assigned work location will be within the PG&E Service Territory.Reporting RelationshipThis position reports to the Director, Enterprise Decision Science/Data Science & Analytics Products.Job Responsibilities:Develop and document the standards ML DevOps pipelines for training, testing, deployment, and monitoring of machine learning models.Extract, transform, and load data from dissimilar sources from across PG&E for their machine learning feature engineering.Support the application of data science/machine learning/artificial intelligence methods to develop defensible and reproducible predictive or optimization models.Support and implement the ML model governance and monitoring of model performance in production.Support the development of mathematical models and AI simulations which represent complex business problems.Write and document python code for data science (feature engineering and machine learning modeling), and ML DevOps under senior data scientist guidance.Contribute to the development of summary presentations.Communicate technical information clearly to other data scientists.Qualifications :Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field2 years in data science (or no experience, if possess Master's Degree)Desired:Master's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent fieldRelevant industry experience (electric or gas utility, renewable energy, analytics consulting, etc.)Knowledge, Skills, Abilities and (Technical) CompetenciesFamiliarity with data science and ML DevOps standards and processes (model evaluation, optimization, feature engineering, model deployment, monitoring, etc.) along with best practices to implement them.Knowledge of software engineering, statistics, and machine learning techniques as they apply to data science modeling and deployment.Knowledge of commonly used data science and/or operations research programming languages, packages, and tools.Hands-on knowledge and application of data science/machine learning models and algorithms.Ability to clearly communicate complex technical details and insights to colleagues and stakeholders.Knowledge of the mathematical and statistical fields that underpin data science.Knowledge of systems thinking and structuring complex problems.Ability to collaborate and/or work on a team.
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