SoCalGas is looking to derive operational insights, enhance decision-making, and provide a competitive advantage by analyzing extensive datasets. The role will apply various analytical and statistical methods, including predictive models and optimization algorithms, to meet business needs and present findings to stakeholders to ensure actionable results aligned with business objectives.
Requirements
- 5 years of data science or statistical analysis-related experience, including: machine learning algorithms, mathematics, research, conducting data experiments, interpreting models, evaluating trends, and statistical outcomes, is required
- 5 years of experience with statistical modeling tools such as SAS, SPSS, R, Python, or other statistical tools and/or programming languages (included in overall years of experience) is required.
- 5 years of experience with ETL, data wrangling, and big data (included in overall years of experience) is required.
- 5 years of experience working with ML services in one of the 3 major cloud providers: GCP, Azure, or AWS (included in overall years of experience) is required.
- 5 years of Domain experience in data trends on the electric and gas networks (included in overall years of experience) is preferred.
- Capabilities in statistics and quantitative research is required
- Capable of assisting in solving business problems through data analytics and analysis is preferred.
Responsibilities
- 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.
Other
- Acts as a bridge between business clients and technical teams
- Presents solutions and findings to the organization.
- Communication skills, written and verbal is required.
- Business acumen, coupled with the ability to interrogate data to address business problems is required.
- Bachelor's degree in mathematics, statistics, computer science, physics, finance or engineering or related degree or equivalent experience is required.
