Description

Our client is an energy infrastructure company focused on the development, construction, and operation of energy storage assets in wholesale electricity markets. Formed in 2017, the company is a national leader in energy storage deployment, utilizing its proprietary dispatch optimization applications to maximize the value of our storage deployments to the grid. Backed by a major Infrastructure fund, they have a strategic and established portfolio of over 1,400 megawatt hours of utility-scale energy storage projects operating or in construction in the U.S., with a leading pipeline of over 11,000 megawatts in active development.

Our client seeks to hire a highly motivated and experienced professional as its Principal Data Scientist. The successful candidate will lead the team's data science initiatives, leveraging deep domain knowledge and hands-on experience in data engineering, machine learning and artificial intelligence to drive innovation and optimization across the organization.

This role will be based out of our Houston, Texas office and will be in office 3/5 days per week.

Key Responsibilities

• Develop and implement advanced machine learning and AI models to optimize energy storage operations and market strategies through deep domain knowledge of mathematics, statistics behind the model structure and hyper parameters.
• Maintain and enhance real time models for power market for proprietary dispatch optimization applications, ensuring they leverage the latest advancements in AI and machine learning
• Communicate complex technical concepts to non-technical stakeholders, providing insights and recommendations to support strategic initiatives.
• Conduct thorough research and stay updated on the latest trends and technologies in data science, AI, and energy storage.
• Mentor and guide junior data scientists, fostering a culture of continuous learning and improvement within the team.
• Collaborate with cross-functional teams, including engineering, finance, and operations, to identify data modeling solutions.

Requirements

• Ph.D. in Mathematics, Statistics, Computer Science, or a related field.
• 10+ years of experience in data science, machine learning, data engineering.
• Deep understanding of the mathematics & statistics behind machine learning models and AI.
• Hands-on experience with a variety of machine learning frameworks and platform (e.g., TensorFlow, Keras, PyTorch).
• Successful track records of machine learning projects with full model life cycle management leveraging DataOp and MLOp best practices.
• Strong programming skills in languages such as Python, C##.
• Extensive experience with cloud computing platforms (e.g., AWS, Google Cloud, Databricks) and big data technologies (e.g., Hadoop, Spark).
• Knowledge of optimization techniques and their application in energy storage operations.