Manager, Data Science

Full Time

Job Title: Manger, Data Science
Department: Market Operations
Reports to: VP of Market Operations
Direct Reports: 0
Date Posted: May2023
Location: Houston, TX or remote
Travel: 10%

Position Purpose:
This is a full-time, exempt position that will be reporting to the VP of Market Operations. This individual will be responsible for developing, evaluating, and improving forecasting models to support Key Capture Energy’s automated energy storage day-ahead and real-time bidding software, which is currently operational in the Electric Reliability Council of Texas (“ERCOT”) market and is expanding into other ISOs. This person will work closely with the software development and market operations teams to use large-scale datasets for model development and deploy those models to production.

Key Responsibilities:

  • Develop new forecasting models to support economic optimization of a portfolio of battery energy storage facilities located across the United States.
  • Back test and benchmark in-house and third-party price forecast models in order to select the best model(s) for maximizing market revenue in varied market conditions.
  • Proactively communicate with and coordinate with Market Operations team to prepare for upcoming price events.
  • Build deep understanding of KCE market operations strategy and the relevant opportunities in the markets in which KCE operates.
  • Work closely with the Software Development team to identify and acquire new data necessary to support new models and deploy these models to production.
  • Collaborate with the Nodal Analysis team to create blended forecasting models informed by both production cost model results and statistic/machine learning based methods.
  • Support departmental efforts to minimize regulatory and financial risk in real time operations.
  • All other duties as required.

Work Experience & Requirements:
• 5+ years of experience applying AI/ML techniques to forecasting problems and deploying solutions to support direct operational outcomes. Prior roles should include significant hands-on experience with tasks such as feature engineering, feature selection, and hyperparameter tuning.
• Advanced degree in relevant quantitative field (data science, computer science, engineering, physics, mathematics or related disciplines).
• Experience working within structured AI/ML software development life cycle processes.
• Familiarity with common Python AI/ML libraries (e.g. SciKit-Learn, TensorFlow, etc).
• Energy market familiarity and battery dispatch optimization experience preferred.
• Experience with design, optimization, and implementation of neural network/convolutional neural network models and hidden Markov models preferred.
• Experience with Azure and Microsoft SQL Server; experiencing deploying AI/ML models and systems in a cloud environment preferred.
• Ability to work in Microsoft Office Suite (including Word, Excel, Powerpoint).
• Ability to work in a small team.
• Strong organizational and time-management skills.

Physical Requirements:

  • Prolonged periods of working at a desk and on a computer

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