Senior Data Scientist, Energy Intelligence

Company Description Recognized by Forbes as one of the fastest-growing private companies in the United States, Palmetto believes that choosing to source clean energy from renewable resources like solar power should be a right, not a privilege. As such, we connect homeowners with renewable energy options such as solar power and energy storage systems. Through our marketplace business model, we empower solar sales professionals and solar installation companies with access to our proprietary design platform, financing, customer management system, logistics, and project management. Our #1 focus is a phenomenal experience for our customers and partners, evidenced in our industry-leading Net Promoter Score.

Our employees are our most valuable resource. Palmetto has a promote-from-within culture for talent development. We offer excellent benefits such as unlimited vacation/PTO, medical, dental, and vision coverage, parental leave, and retirement plans.

This role is fully remote in the US

Summary

As a Data Scientist at Palmetto, you will collaborate closely with our product and engineering teams to help our customers take control of their energy. Your primary focus will be to develop and enhance our building energy modeling (BEM) algorithms and capabilities. Your responsibilities will include sourcing, vetting, cleaning, processing, and analyzing large volumes of energy-related data. You will also build and maintain machine learning models, data visualizations, back-end services, APIs, and oversee their deployment. As a key member of the energy intelligence team, you will be relied upon for your data science expertise, but also expected to contribute more broadly to the team’s software development efforts. Your work will directly impact our ability to provide customers and partners with valuable energy insights and actionable recommendations, helping them make informed decisions about energy consumption.

Responsibilities

• Apply statistical and machine learning techniques to solve challenging new problems and improve the accuracy and reliability of existing models.
• Conduct ad-hoc analyses and data explorations to guide the Energy Intelligence roadmap.
• Collaborate with software engineers to integrate prototype models and algorithms into production systems.
• Build and optimize data pipelines to ensure efficient and reliable access to large datasets.
• Contribute to the code review process, provide constructive feedback to peers.

Minimum Qualifications

• Strong quantitative background with a proven track record in scientific computing and statistical analysis.
• Proficiency in Python and the data science stack (e.g., Pandas, NumPy, SciPy, Matplotlib, Seaborn, etc.)
• Proficiency in SQL with experience in relational databases.
• Experience with machine learning techniques and libraries (e.g., scikit-learn, TensorFlow, PyTorch, etc.)
• Knowledgeable about software engineering best practices, including version control, code review, and testing.
• Ability to navigate ambiguity and thrive in a fast-paced environment.

Preferred Qualifications

• Advanced proficiency in Python, with extensive experience in object-oriented programming and writing clean, maintainable code.
• Experience manipulating geospatial data (raster, vector, point clouds), and familiarity with geospatial libraries and tools (e.g., GeoPandas, Shapely, Rasterio, QGIS).
• Familiarity with DevOps practices, including CI/CD pipelines, containerization (e.g., Docker), and cloud computing platforms (e.g., AWS, GCP, Azure).
• Knowledge of MLOps practices, including model deployment, monitoring, and scaling machine learning models in production environments.
• Experience designing and building, and maintaining data-focused APIs, with an understanding of RESTful principles.
• Experience working in the clean energy space, or with home energy data.

Equal Employment Opportunity

Palmetto embraces diversity and is an Equal Employment Opportunity employer. Employment is decided on the basis of qualifications, merit, and business need. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or any other status protected under federal, state, or local law.

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