Data Science, Habitat Energy

• This multifaceted position requires both analytical skills to enhance our modeling capabilities and practical know-how to translate these models into commercial value
• Bachelor’s Degree in Physics, Chemistry, Computer Science, Data Science, Engineering, or a related field
• Strong analytical skills, problem-solving abilities, proficiency in Python
• Proficiency in Python and familiarity with data science and optimization libraries (cvxpy, pandas/polars, gradient boosted tree libraries, pytorch)
• Deep desire to learn about the energy markets, particularly as it relates to battery technology
• Strong communication skills, ability to work collaboratively within and across teams

Desirable

• This role will bridge the gap between commercial insights and technical execution, and battery modeling expertise, supporting the data science team by contributing to both the development and operational stages of our projects
• You will help develop and refine models that predict battery performance, degradation, and site-specific optimization parameters while maintaining and optimizing our live battery systems using our DS software stack
• Developing and validating battery performance and site-specific predictive models to predict degradation, efficiency, and optimize operations based on local conditions
• Performing both technical and content quality assurance on BESS/DART Optimizer and backtest frameworks
• Conducting ad-hoc analysis and applying data science models to support business decisions
• Operational management of live battery optimization systems, addressing issues promptly and efficiently
• Collaborating with the commercial team to build and maintain predictive pricing models keeping abreast of new market drivers