The Load Research and Retail Settlement team utilizes statistical analysis, data modeling, and machine learning algorithms to study customer load patterns in order to support various critical business functions including, Load Forecasting, Production Cost Modeling, Transmission and Distribution Planning, Cost of Service Studies and Rate Design, and Energy Efficiency.
Additionally, the team manages the calculation and submission of energy and capacity data to the New York Independent System Operator (NYISO) each month to enable settlement of the energy and capacity markets.
The Data Scientist role will support Load Research initiatives by utilizing data science methods and AWS tools to derive insights into customer usage from AMI meter, customer, and geospatial data sources.
Job Responsibilities
- Produce class average load profiles from AMI meter data using accepted industry techniques to support Rate Design, Cost of Service Studies, Energy Efficiency, Load Forecasting, and Retail Settlement
- Design load research and special studies by applying statistical sampling techniques and theory
- Design, develop, and implement analytical models and visualizations to provide insight into customer usage patterns
- Support monthly energy and capacity market settlement in NY State by calculating and submitting energy and capacity data for all Load Serving Entitles on Long Island (NYISO Zone K)
- Utilize statistical models and machine learning algorithms to disaggregate end-use load from whole premise load data collected by AMI meters
- Perform regression modeling to produce weather normalized load shapes
- Build data pipelines to validate, clean, and transform large data sets to support Load Research analytics use cases
- Effectively communicate results of analytical models to technical and non-technical stakeholders
- Consult to other business groups on data science techniques
Job Specific Qualifications
Required
- Bachelor's degree in mathematics, statistics, data science/analytics, engineering, computer science or a related quantitative field with at least 5 years of Load Research or similar quantitative analysis experience
- Demonstrated statistical analysis and data modeling skills including experience with sampling methods, regression, clustering, and time series analysis
- Ability to efficiently clean and validate large data sets for analysis
- Proficient in a data science programming language (SAS, Python, SQL or similar)
- Experience using visualization tools (Tableau, Power BI, or similar)
- Strong knowledge of electric usage patterns at various levels, including system, customer class, and end use
- Experience or certification in Machine Learning
- Excellent written and verbal communication skills including the ability to speak to higher levels of internal leaders, external regulators and other market players. Ability to explain complex technical concepts to non-technical stakeholders
- Knowledge of energy and capacity markets, preferably NYISO
- Experienced with weather normalization of electric load
- Knowledge of Load Research best practices, Demand Side Management, and Energy Efficiency programs
- Advanced Excel skills
- Knowledge of AWS tools (Sagemaker, Glue, etc.)
- Strong attention to detail and the ability to handle time sensitive deliverables requiring a high degree of accuracy
Desired
- Masters degree in mathematics, statistics, data science/analytics, engineering, computer science or a related quantitative field.
- Familiarity with electric load forecasting, cost of service studies, and rate design preferred.
- Experience providing testimony in rate case proceedings a plus
Minimum Years of Experience
5 years of experience
Education
Bachelors
Public Service Enterprise Group (PSEG)
New York United States
www.pseg.com
