SDG&E is an innovative San Diego-based energy company that provides clean, safe and reliable energy to better the lives of the people it serves in San Diego and southern Orange counties. The company is committed to creating a sustainable future by providing its electricity from renewable sources; modernizing natural gas pipelines; accelerating the adoption of electric vehicles; supporting numerous non-profit partners; and, investing in innovative technologies to ensure the reliable operation of the region’s infrastructure for generations to come. SDG&E is a subsidiary of Sempra Energy (NYSE: SRE).

Our highly trained and responsive employees with their diverse skills, talents and ideas are the reason we can deliver on our commitment and are building America’s best energy company. They are also the reason why we have been recognized with the industry’s most coveted awards. Our employees undertake challenging work, and receive highly competitive compensation and benefits. As one of the region’s largest employers, we’re always searching for talented and bright people to join our team. After all, it takes the best to build the best. Learn more about benefits HERE.

Diversity and inclusion are core values of SDG&E. Empowering our employees to be their whole selves at work is our competitive advantage. This is where new ideas come from and meaningful collaboration gets an authentic start. By bringing together people with different perspectives, diverse backgrounds and real commitment to their own individuality, we have built a stronger business. Learn more about our commitment to diversity and inclusion HERE.

For more information, visit SDGEnews.com or connect with SDG&E on Twitter (@SDGE), Instagram (@SDGE) and Facebook.

Primary Purpose

The Data Scientist collaborates with business subject matter experts and data engineers to correlate and sift through a large variety and volume of data types and sources with the goal of discovering insights and patterns to address a pressing business problem or provide a competitive advantage for the business. After extracting data, the Data Scientist will apply advanced statistical and computational methods to formulate models and algorithms to address the business need, and will subsequently communicate results, conclusions and recommendations across the organization.

Duties and Responsibilities

• Proactively partner with business to identify use-cases, determine ROI, and prioritize them accordingly.
• Design, Develop, test, evaluate, tune, and deploy predictive and machine learning models and algorithms.
• Coordinate with data engineers to acquire, extract, transform, manage and manipulate data sets for specific use cases.
• Present the rationale of findings, recommendations, and methodologies used in business terms.
• Educate team members and IT organization and business users about how and when data science can be leveraged to solve business problems.
• Create clear documentation of workflows, process flows, methodologies used.
• Stay current with data science trends and open source libraries.
• Performs other duties as assigned (no more than 5% of duties).

Required Qualifications

• Bachelor’s Degree Mathematics, Statistics, Computer Science, Physics, or Engineering.
• Master’s Degree Mathematics, Statistics, Computer Science, Physics, or Engineering.
• Ability to use a computer, keyboard and mouse 6-8 hours per day.
• 5 years experience with a strong background in statistical analysis, machine learning algorithms, mathematics, research, or equivalent job experience.
• Experience in conducting data experiments, interpreting of models, evaluating of trends, and statistical outcomes.
• In depth working knowledge of data science/statistical tools such as Python, Spark, SAS, SPSS, or R, as well as analytical documentation, such as Jupyter or iPython notebook.
• Demonstrate capabilities in statistics and quantitative research.
• Experience in extraction, transforming, loading (ETL) technologies.
• Familiarity with neural networks, deep learning, Naive Bayes, regression, random forest, clustering, text mining, social network analysis.
• Working knowledge of major machine learning frameworks: Tensorflow, Pytorch, or Keras.
• Familiarity with supervised and unsupervised machine learning.
• Requires strong business acumen and curiosity, coupled with the ability to interrogate data to address business problems.
• Domain knowledge in the Utilities industry.
• Strong problem-solving and metadata skills.
• Excellent written and communication skills explaining complex quantitative models to business, management and IT stakeholders.

Preferred Qualifications

• Experience working with ML services in one of the 3 major cloud providers is a plus: Azure, Google or AWS.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, citizenship, disability or protected veteran status.