Darum lohnt es sich
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.
Responsibilities 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.
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. #J-18808-Ljbffr
