Data Scientist/Predictive Analytics Specialist

Position Overview

Become a Data Scientist/Predictive Analytics Specialist at Southern California Edison (SCE) and build a better tomorrow. In this role you will work closely with internal clients, subject matter experts, data engineers, process leads, project/program managers, and other teams to turn data into actionable insights that support informed business decisions. You will work in the Business Intelligence Center (BIC) within Customer Service to develop predictive analytics solutions, support internal clients by applying advanced analytics to solve business challenges, and enhance both business and customer experiences. You will analyze large datasets, build predictive models, and generate insights that improve decision-making while partnering with OU clients to ensure that analytics solutions deliver measurable business value and align with organizational goals.

Key Responsibilities

• Collaborate with team members and stakeholders to support solutions for data-driven business challenges.
• Build and implement predictive and prescriptive models to improve decision-making.
• Assist in identifying opportunities for AI, machine learning, and data science to address business needs.
• Translate defined business objectives into actionable requirements for AI/ML models.
• Contribute to the design and development of AI/ML models using established techniques and frameworks.
• Apply machine learning algorithms and data mining methods to analyze datasets and generate insights.
• Monitor model performance and support enhancements to maintain accuracy and reliability.
• Follow established processes and governance standards for ethical, explainable, and reproducible AI/ML solutions.
• Stay informed on emerging tools and techniques and share recommendations with the team.
• Participate in team knowledge-sharing and professional development activities.
• Ensure compliance with security and integrity standards when handling sensitive data and assets.
• Collaborate with SCE stakeholders, including project sponsors, data analysts, and subject matter experts, to understand key business problems and desired outcomes.
• Work with experienced data scientists and analytic leaders to develop solutions for complex, data-intensive business issues.
• Identify, assess, and prepare internal and external data sources for analysis by cleaning, merging, filtering, transforming, or enriching data as needed.
• Validate analysis findings through iterative testing and by gathering stakeholder feedback.
• Present insights, assumptions, validation results, and recommendations in clear, business-friendly language using data visualization techniques.
• Propose innovative data mining methodologies to uncover new perspectives from existing data sources.
• Keep abreast of current data science and big data techniques while ensuring the highest standards when handling sensitive information.

Required Qualifications

• Bachelor's Degree (or higher) in a quantitative discipline such as Computer Science, Electrical Engineering, Statistics, Mathematics, or Business Analytics.
• One or more years of experience analyzing or manipulating complex data.

Preferred Qualifications

• Bachelor's Degree (or higher) in an Applied Sciences or STEM discipline.
• Industry certifications in data science, machine learning, or cloud analytics (e.g., AWS Certified Machine Learning, Microsoft Certified Data Scientist).
• Experience with cloud-based analytics platforms (e.g., AWS, Azure, GCP).
• Proficiency in Python or R for machine learning and predictive modeling.
• Familiarity with big data technologies such as Snowflake and Databricks.
• Knowledge of AI/ML frameworks and libraries.
• Strong understanding of data visualization tools (e.g., MS Platform Technologies, Power BI, Tableau).
• Experience integrating predictive analytics into business processes for measurable impact.
• Experience developing or deploying Gen AI-based solutions (e.g., prompt engineering, summarization, text classification, or workflow automation).
• Excellent problem-solving skills and the ability to communicate technical concepts to non-technical stakeholders.

Benefits & Perks

• Hybrid Work Mode: Enjoy flexible working with a mix of on-site and remote days.
• Professional Growth Opportunities: Engage in knowledge-sharing and career development initiatives.
• Meaningful Impact: Contribute to the Clean Energy Revolution by powering projects that reduce carbon emissions and create cleaner air.
• Equal Opportunity: Be part of an inclusive environment committed to diversity and providing reasonable accommodations.