Senior Data Scientist
New
Fully remote work opportunity for candidates based in the United States or Canada.Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5–8+ years
- Required Skills
- PythonSQLMachine LearningNumpyPandasscikit-learn
Requirements
- 5–8+ years of relevant data science experience after completing a Bachelor’s degree.
- Strong expertise in supervised and unsupervised machine learning techniques and statistical modeling approaches.
- Experience applying data science to energy systems, demand response, or distributed energy resources.
- Advanced proficiency in Python and SQL with experience building production-ready solutions.
- Strong experience with Python data science libraries such as pandas, NumPy, SciPy, and scikit-learn.
- Experience working with time-series data, panel data analysis, and predictive modeling.
- Strong data visualization skills and ability to communicate analytical findings clearly.
- Ability to balance analytical rigor with practical engineering considerations.
- Strong communication skills with the ability to explain complex concepts to diverse audiences.
- Ability to collaborate effectively with technical teams and influence cross-functional stakeholders.
Responsibilities
- Lead the design, development, and refinement of statistical and machine learning models for load forecasting, flexibility analysis, and energy resource optimization.
- Analyze large-scale datasets, including smart meter data, customer information, and grid attributes, to support strategic decision-making.
- Improve existing models and develop new predictive capabilities for deployment in production environments.
- Validate models through structured testing methods, including backtesting, cross-validation, and uncertainty analysis.
- Collaborate with data scientists, engineers, and energy domain experts to ensure solutions reflect real-world conditions.
- Translate customer requirements and industry challenges into reusable data products and platform capabilities.
- Develop clean, efficient, maintainable code and documentation for reproducibility and scalability.
- Communicate analytical assumptions, limitations, and insights effectively to technical and non-technical stakeholders.
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