Senior Forecasting and Optimization Engineer
$150,000–$175,000 year
On-siteBrooklyn, New York, United States
Brooklyn, New York, United StatesOn-sitePart Time$150,000–$175,000 yearSenior LevelDoctorate Or Professional DegreeSaaSSmall
Part TimeSenior LevelDoctorate Or Professional DegreeSmallSaaS
Job Summary
Develop and improve accurate energy forecasting models and control optimization algorithms. Design, write, test, and deploy production-grade code for mission-critical forecasting products. Build tools to monitor operational model quality and translate data from large distributed energy datasets into actionable insights for utilities. Provide guidance on machine learning and optimization methods while presenting results to internal and external stakeholders. Collaborate with Data Engineering, Client Success, and Product teams to solve difficult problems in distributed energy.
Required Qualifications
- Passion for enabling a carbon-free, distributed energy future
- At least five years of experience in machine learning, statistical analysis, data visualization, control systems engineering, and/or mathematical optimization
- Experience developing data pipelines using large-scale relational databases
- Strong mathematical skills, with the ability to apply new mathematical techniques to real-world problems
- At least three years of hands-on experience with Python and the scientific and machine learning tool stack (Pandas, Numpy, SciPy, Sklearn, PyTorch, and Tensorflow)
- An ability to find valuable insights in large, complex datasets
- Ability to explain results from large-scale data analyses to diverse audiences in a way that is clear, interesting, and actionable
- Ability to have fun while working on really hard problems with really smart people
Desired Qualifications
- Experience bringing long-term research projects, such as an MS or PhD thesis, to a successful conclusion
- Experience building large-scale timeseries forecasting models in a commercial software setting
- Experience developing control and optimization solutions for large-scale problems
- Experience building large-scale forecasting and machine learning products in the cloud (e.g., AWS, GCP, Azure, Snowflake, Databricks)
- A strong background in mathematics and statistics
- Experience using Large Language Models to accelerate software development and reliably add new capabilities to real products
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