Data Scientist, Advisor

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This range is provided by Southern California Edison (SCE). Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range $/yr - $/yr

Join the Clean Energy Revolution Become a Data Scientist, Advisor at Southern California Edison (SCE) and build a better tomorrow. In this job, you’ll partner closely with business and operational teams across the enterprise to identify, design, and deliver data-driven solutions that improve safety, efficiency, reliability, and cost effectiveness. You will support a diverse portfolio of use cases by working across the full data science lifecycle from problem discovery and data exploration through model development and deployment.

You will apply strong technical and analytical skills in a pragmatic environment, where success depends on both modeling expertise and the ability to translate business problems into actionable and production-ready solutions. In addition to delivering individual use cases, you will also play a key part in evolving data science infrastructure, enhancing data science capabilities, building tools, and establishing best practices.

As a Data Scientist
, your work will help power our planet, reduce carbon emissions and create cleaner air for everyone. Are you ready to take on the challenge to help us build the future?

• Cooperates with various stakeholders across the organization to understand and define solutions for complex, data-intensive business problems requiring advanced analytics
• Facilitates the development of predictive and prescriptive models using cutting-edge techniques to derive impactful insights and guide data-driven decision making
• Identifies and implements new data collection sources and methods to build robust datasets for modeling
• Leads data preparation and integration processes for large, varied datasets; ensures data quality and integrity
• Drives selection and preparation of data tailored to specific business use cases and analytics projects
• Leads development and enhancement of advanced analytical models using statistical, algorithmic, data mining and visualization techniques to uncover insights
• Improves existing quantitative models leveraging latest analytical tools and techniques using novel AI/ML trends
• Performs sophisticated analytics and translates outputs into understandable, actionable insights and recommendations for stakeholders
• Researches industry trends and emerging tools, methods and models; provides insights on their potential business application and adoption
• Continues developing data science relationships and participating in industry groups and events to stay current on techniques
• Ensures the protection of all physical, financial and cybersecurity assets, and properly accesses and manages private customer data, proprietary information, confidential medical records, and other types of highly sensitive information and data with the highest standards of conduct and integrity

• Bachelor's Degree (or higher) in a quantitative discipline such as Computer Science, Electrical Engineering, Statistics, Mathematics, or Business Analytics
• Five or more years of experience in data analytics related work (PhD in Computer Science, Electrical Engineering, Statistics, Mathematics, business analytics = 2 years of experience credit)

• Experience designing and delivering production-grade data science or AI/ML solutions, including conventional machine learning and deep learning approaches such as computer vision and large language models, applied to real-world operational and business problems
• Experience leading the end-to-end model development lifecycle, including problem formulation, method selection, data exploration, feature engineering, model training and evaluation, and deployment of production-ready solutions
• Hands-on experience working with diverse data types and formats, including tabular and time-series data, imagery, video, LiDAR or other spatial data, and unstructured text or audio recordings
• Experience using cloud-based data and AI/ML platforms (e.g., GCP, Azure, AWS)
• Ability to balance individual ownership with effective collaboration across cross-functional teams
• Demonstrated operational mindset, balancing technical rigor with practical constraints such as data quality, system dependencies, timelines, budget, and evolving business needs
• Strong client-facing and stakeholder engagement skills, with experience leading problem discovery discussions and translating complex business needs into well-scoped analytical and AI solutions
• Curiosity and ability to stay current with emerging data science and AI technologies, with a pragmatic approach to evaluating and adopting new methods and tools for development and production use in an operational environment

• This position’s work mode is hybrid. The employee will report to an SCE…