The Data Science Modeling intern will provide support to Project Managers on utility energy data projects related to predictive analysis, disaggregation research, and model development by applying statistics, mathematical/machine learning approaches, and testing/training the model/approach using available data. The responsibilities of this position include data cleansing, normalization, and transformation of data before performing data analysis and building/developing data-based models. SQL database querying and applying statistical approaches such as multi-variate regression, clustering, and/or other predictive approaches to extract learnings from data and answer research questions as laid out in the project is a key responsibility of the position.
Education, Skills & Experience:
-
Master’s or PhD student with a background in Math, Statistics, computer science, engineering, or data sciences is preferred
-
Strong knowledge of computational statistics, and machine learning approaches along with proficiency in data mining and transformation is required
-
Ability to build/write code in Python/R to apply machine learning and other self-learning techniques leveraging large datasets is strongly preferred
-
Knowledge of Revealed Preferences Theory and applicational experience is a plus
-
Powerpoint presentation skills required