Senior Data Scientist (Perf. Mgmt & Org. Strategy) (Hybrid Schedule)

at  SoCalGas

Primary Purpose
Interfaces 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. Applies advanced statistical and computational methods to formulate models and algorithms to address the business need, and communicates results, conclusions and recommendations across the organization. Provides work direction to junior subordinate data scientists and business analysts within the department. Contributes to the adoption of advanced data science and analytics across the business. Works with relevant stakeholders through quantitative analytics, and the application of appropriate advanced analytics, for assigned business’s key initiatives.

Duties and Responsibilities

• Identifies and formulates use-cases, determines ROI, and prioritizes them accordingly.
• Conducts assessments of the use-cases to determine feasibility on major projects that are leveraging data science.
• Advises business stakeholders about the conclusions drawn from data science projects.
• Oversees the activities of subordinate data scientists and business analysts within the department. This could include hiring, training, developing skills, evaluating performance, counseling and correcting performance, motivating employees to achieve production and quality objectives.
• Advises team members, IT organization, and business users about how and when data science can be leveraged to solve business problems.
• Coordinates with data engineers to retrieve and evaluate the different data sets.
• Develops, tests, evaluates, and tunes predictive and machine learning models.
• Presents at conferences on behalf of the company.
• Stays current with data science trends.
• Performs other duties as assigned (no more than 5% of duties).

Qualifications

Education

• Bachelor’s Degree Mathematics, Statistics, Computer Science, Physics, or Engineering. Required
• Master’s Degree Mathematics, Statistics, Computer Science, Physics, or Engineering. Preferred Experience
• 7 years Data science or statistical analysis related experience including: machine learning algorithm, mathematics, research, conducting data experiments, interpreting models, evaluating trends and statistical outcomes. Required
• Experience in extraction, transforming, loading (ETL) technologies. Preferred
• Experience working with ML services in one of the 3 major cloud providers: GCP, Azure, or AWS. PreferredKnowledge, Skills and Abilities
• Communication skills, written and verbal. Advanced Required
• Business acumen, coupled with the ability to interrogate data to address business problems. Advanced Required
• Ability to communicate findings and recommendations to senior business leadership. Advanced Preferred
• Capabilities in statistics and quantitative research. Intermediate Required
• Capable of assisting in solving business problems through data analytics and analysis. Intermediate Preferred
• Domain knowledge in the utilities industry. is a plus. Intermediate Preferred

Equal Opportunity Employer Minorities/Women/Protected Veterans/Disable

• Identifies and formulates use-cases, determines ROI, and prioritizes them accordingly.
• Conducts assessments of the use-cases to determine feasibility on major projects that are leveraging data science.
• Advises business stakeholders about the conclusions drawn from data science projects.
• Oversees the activities of subordinate data scientists and business analysts within the department. This could include hiring, training, developing skills, evaluating performance, counseling and correcting performance, motivating employees to achieve production and quality objectives.
• Advises team members, IT organization, and business users about how and when data science can be leveraged to solve business problems.
• Coordinates with data engineers to retrieve and evaluate the different data sets.
• Develops, tests, evaluates, and tunes predictive and machine learning models.
• Presents at conferences on behalf of the company.
• Stays current with data science trends.
• Performs other duties as assigned (no more than 5% of duties)