Data Scientist II (Hybrid Schedule)

About Us

SoCalGas, the nation’s largest gas distribution utility, is dedicated to providing safe, reliable, and affordable energy to over 21 million Southern California customers. Through innovation, collaboration, and a unwavering commitment to the needs of our communities we proudly uphold our mindset of “Glad to be of Service” and provide exceptional customer service today and ready to meet California’s energy needs with innovative solutions for tomorrow.

As an employee of SoCalGas, you will support our core values to do the right thing, champion people, and shape the future. You will play a pivotal role in the energy transition initiatives, supporting our mission: Safe, reliable, and affordable energy delivery today. Ready for tomorrow. We are committed to attracting top talent and fostering a diverse workforce that reflects the vibrant communities we serve.

As an employee of SoCalGas, you’ll enjoy a competitive compensation plan, upward mobility opportunities and the ability to find a true work life balance. Discover the rewards of joining SoCalGas by exploring our website: Our Mission; Sustainability, In the Community, and Employee Benefits. Join SoCalGas today and become a vital part of a team that is driving innovation, championing community needs, and shaping the future of energy in California.

Acts as a bridge between business clients and technical teams, analyzing extensive datasets to derive operational insights, enhance decision-making, and provide a competitive advantage. The role will apply various analytical and statistical methods, including predictive models and optimization algorithms, to meet business needs. The role involves presenting findings to stakeholders and business SMEs, ensuring actionable results aligned with business objectives. Collaboration with data scientists, data engineers, and BI analysts is essential to drive innovation in data science and analytics across the organization.

- Develops, trains, and maintains predictive models including, but not limited to Linear Regression, Logistic Regression, KNN, Random Forest, XGBoost, SVM, ARIMA, Neural Networks, and other industry leading pattern recognition models. Possesses strong working knowledge with statistical testings including, but not limited to, T-tests, ANOVA, Chi-Square, Non-parametric tests, A/B testing, and Bayesian inference.

- Creates and tests modeling scenarios for business processes, requirements, budgets, and regulatory impacts. Responds to data requests for regulatory filings, financial planning, and data science projects. Advises business stakeholders on data science project conclusions and collaborate on implementation.

- Works with data engineers, business SMEs, and BI analysts on data science projects to advance analytics maturity.

- Stays current with data science and AI trends.

- Communicates and interprets analytical outcomes to address business problems. Presents solutions and findings to the organization.