Roles and Responsibilities

• Monitor and analyze data to uncover optimization gaps
• Develop high-performance algorithms, machine learning models, or other methodologies to close optimization gaps.
• Identify performant features and models and make them universally accessible to our teams across EE.
• Provide technical leadership to our team by reviewing problem sets, proposing prediction models, and reviewing experiments and models.
• Act as a resident expert for machine learning, statistics, and experiment design.

Desired Candidate Profile

• Experience in experiment design and applied machine learning predicting outcomes in large-scale, complex datasets.
• Proficiency in Python, Azure ML, or other statistics/ML tools.
• Proficiency in Deep Neural Network, Python based frameworks.
• Proficiency in Azure Data Bricks, Hive, Spark.
• Proficiency in deploying models into production (Azure stack).
• Moderate coding skills. SQL or similar required. C# or other languages strongly preferred.
• Strong drive for results. You have a proven record of shepherding experiments to create successful shipping products/services.
• Experience with prediction in adversarial (energy) environments highly desirable.
• Understanding of the model development ecosystem across platforms, including development, distribution, and best practices, highly desirable.