Data Scientist Advisor

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 Advisor, 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? Responsibilities

• 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.
• A material job duty of all positions within the Company is ensuring the protection of all its physical, financial and cybersecurity assets, and properly accessing and managing 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.

Preferred Qualifications

• Intensive experience developing and deploying advanced AI solutions, with significant expertise in computer vision, including image and video analytics, object detection, classification, segmentation, anomaly detection, and multimodal AI applications in production environments.
• Experience designing, implementing, and operationalizing Generative AI and Agentic AI solutions, including large language models (LLMs), retrieval-augmented generation (RAG), AI orchestration frameworks, autonomous workflows, and multi-agent systems that deliver measurable business value.
• Experience leading the end-to-end AI/ML lifecycle, including problem formulation, solution design, data exploration, feature engineering, model development, evaluation, deployment, monitoring, and ongoing model lifecycle management in production environments.
• Experience with MLOps and cloud-based AI/ML platforms (e.g., GCP, Azure, AWS), including scalable data and model pipelines, CI/CD processes, model governance, automated retraining, performance monitoring, and production support.
• Experience working with diverse data modalities, including structured and time-series data, imagery, video, LiDAR or geospatial datasets, text, audio, and other unstructured data sources.
• Strong consulting, communication, and stakeholder engagement skills, including experience leading problem discovery discussions, translating complex business challenges into well-scoped AI solutions, and influencing technical and business decision-making across cross-functional teams.
• Demonstrated operational mindset with the ability to balance technical rigor, innovation, scalability, reliability, cybersecurity, cost, timelines, data quality, and evolving business priorities when delivering enterprise AI/ML solutions.
• Experience providing technical leadership for complex AI/ML initiatives, including influencing solution architecture, establishing best practices and technical standards, mentoring data scientists, and driving adoption of scalable AI capabilities across multiple projects and teams.