Data Scientist, Forecasting – Energy Storage System Optimization
Job Description:
• Develop, implement, and deploy machine learning models and statistical analyses to optimize energy storage and solar asset performance across Stem's portfolio
• Design and build data pipelines to extract, transform, and analyze large-scale datasets from energy systems
• Collaborate with software engineering, product management, and energy experts to integrate data-driven solutions into PowerTrack platforms
• Create data visualizations, dashboards, and reports to communicate insights and recommendations to stakeholders
• Conduct exploratory data analysis to identify trends, patterns, and opportunities for improving system performance and business outcomes
Requirements:
• Minimum of 1-3 years in data science, analytics, machine learning, or related field
• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related field, or equivalent experience
• Proficiency in Python and data science libraries (pandas, numpy, scikit-learn, TensorFlow or PyTorch)
• Familiarity with optimization libraries (e.g. CVXPY) and experience formulating or interpreting constrained optimization problems
• Strong SQL skills and experience working with large datasets using SQL or SQL-like query languages.
• Comfortable using modern AI coding assistants (Cursor, Claude Code, GitHub Copilot, etc.) to accelerate development
• Experience writing well documented, well tested, and maintainable code
• Version control with Git and experience using GitHub, GitLab, or Bitbucket
• Experience prototyping analyses in Jupyter notebooks and building lightweight data applications to explore and communicate insights, using tools such as Matplotlib, Seaborn, Plotly, and frameworks like Streamlit or Dash.
• Strong analytical and problem-solving skills with expertise in statistical methods and machine learning algorithms
• Excellent communication and presentation abilities with capacity to translate complex technical findings for diverse audiences.
Benefits:
• Full health benefits on the first day of employment (several medical plan options-HDHP and PPO, dental plans, FSA/HSA-with employer contribution, employer paid vision/LTD/STD/Life, variety of voluntary coverage)
• 401k (pre- or post-tax) on first day of employment
• 12 paid calendar holidays per year
• Flexible time-off
• Develop, implement, and deploy machine learning models and statistical analyses to optimize energy storage and solar asset performance across Stem's portfolio
• Design and build data pipelines to extract, transform, and analyze large-scale datasets from energy systems
• Collaborate with software engineering, product management, and energy experts to integrate data-driven solutions into PowerTrack platforms
• Create data visualizations, dashboards, and reports to communicate insights and recommendations to stakeholders
• Conduct exploratory data analysis to identify trends, patterns, and opportunities for improving system performance and business outcomes
Requirements:
• Minimum of 1-3 years in data science, analytics, machine learning, or related field
• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related field, or equivalent experience
• Proficiency in Python and data science libraries (pandas, numpy, scikit-learn, TensorFlow or PyTorch)
• Familiarity with optimization libraries (e.g. CVXPY) and experience formulating or interpreting constrained optimization problems
• Strong SQL skills and experience working with large datasets using SQL or SQL-like query languages.
• Comfortable using modern AI coding assistants (Cursor, Claude Code, GitHub Copilot, etc.) to accelerate development
• Experience writing well documented, well tested, and maintainable code
• Version control with Git and experience using GitHub, GitLab, or Bitbucket
• Experience prototyping analyses in Jupyter notebooks and building lightweight data applications to explore and communicate insights, using tools such as Matplotlib, Seaborn, Plotly, and frameworks like Streamlit or Dash.
• Strong analytical and problem-solving skills with expertise in statistical methods and machine learning algorithms
• Excellent communication and presentation abilities with capacity to translate complex technical findings for diverse audiences.
Benefits:
• Full health benefits on the first day of employment (several medical plan options-HDHP and PPO, dental plans, FSA/HSA-with employer contribution, employer paid vision/LTD/STD/Life, variety of voluntary coverage)
• 401k (pre- or post-tax) on first day of employment
• 12 paid calendar holidays per year
• Flexible time-off