Senior Data Scientist, PV Performance & Diagnostics

What We Are Looking For / Role Overview

Stem is seeking a Senior Data Scientist with strong hands-on experience in solar PV performance modeling to join our team. This role is focused on advancing performance analytics for solar PV and battery energy storage within PowerTrack, Stem's core asset management platform. You will be responsible for supporting and standardizing the physics-based performance models, underperformance and loss reporting, and expected-energy forecasting that our customers rely on. A solid foundation in statistics and machine learning (ML) is expected, with room to grow into more advanced ML-based techniques as your role here develops.

Key Responsibilities

• Lead the design, implementation, and continuous improvement of physics-based performance models for solar PV and battery energy storage assets within PowerTrack, including the underlying data configuration and validation that keep model inputs accurate and consistent across heterogeneous site layouts
• Own the accuracy and defensibility of performance and losses/underperformance reporting (e.g., downtime, curtailment, soiling, and other loss categories) used for customer reporting and decision-making
• Develop and contribute to time-series forecasting models that support expected-energy prediction and inform downstream merchant operations and storage/hybrid use cases
• Apply and contribute to evaluation frameworks — running structured experiments, validating model accuracy against known or proxy ground truth, and producing the technical documentation, validation reports, and benchmarks that communicate modeling assumptions and findings to technical and non-technical stakeholders
• Partner with software engineers and data engineers to integrate performance models and configuration tooling into production systems that are scalable, testable, and maintainable
• Collaborate with the team's machine-learning-based fault detection efforts, connecting detected anomalies to the underperformance detection and loss categorization work this role owns, and aligning on shared data and system interfaces — with an eye toward this role expanding into ML-driven diagnostics as that capability matures
• Exercise independent judgment on prioritization and technical approach for cross-functional projects with competing constraints, escalating to subject matter experts only when needed, and lead peer reviews of data science artifacts and code — providing constructive feedback and guiding junior data scientists

Required Qualifications

• Minimum of 5 years in data science, analytics, PV/solar performance engineering, or a related quantitative field (3+ years with a PhD in a relevant scientific or engineering discipline)
• Bachelor's degree in Electrical Engineering, Renewable/Solar Energy, Physics, Data Science, Statistics, Computer Science, Mathematics, or a related field; or equivalent experience
• Hands-on experience with solar photovoltaic performance modeling — including tools like pvlib or similar irradiance/PV simulation libraries — translating physical/engineering assumptions into code
• Strong foundation in statistics and machine learning: regression, classification, time-series analysis, hypothesis testing, and model evaluation
• Proficiency in Python and data science libraries (pandas, NumPy, scikit-learn)
• Advanced SQL skills and experience working with large-scale time-series datasets
• Experience building, validating, and benchmarking production-grade models or statistical algorithms — designing informative experiments and translating findings into actionable solutions
• Experience writing well-documented, reproducible, and maintainable scientific code, using Git/version control and modern AI coding assistants (Cursor, Claude Code, OpenAI Codex, etc.) to accelerate development
• Strong communication and presentation skills with the ability to translate complex technical findings for diverse audiences

Preferred Qualifications

• Experience with C#/.NET
• Familiarity with battery operations and modeling
• Experience with data provenance, data quality, or configuration-management practices
• Experience applying time-series anomaly detection and forecasting to IoT, energy monitoring, or other data-intensive operational environments
• Knowledge of cloud platforms (AWS, Azure, GCP) and microservices / containerization (Docker, REST APIs)
• Familiarity with database technologies including PostgreSQL, Timescale, or Redis
• Experience with CI/CD pipelines and agile development methodologies
• Master's degree in a quantitative field

To learn more about Stem, visit our stem.com where you’ll find information about our solutions, technology, partners, case studies, resources, latest news and more. Here are some relevant links:

• Company Overview
• Newsroom
• Insights
• LinkedI

What We Offer:

At Stem, you will work in a growing, innovative, mission-driven company with talented colleagues that have a passion for building renewable energy systems. Stem offers competitive compensation as well as a comprehensive set of benefits to support the health and wellness of our employee including:

• A competitive compensation package, including eligibility for a bonus or commission based on the role.
• 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

Stem, Inc. is an equal opportunity employer committed to diversity in the workplace and does not discriminate against any employee or applicant for employment because of race, color, sex, pregnancy, religion, national origin, ethnicity, citizenship, sexual orientation, gender identity, age, marital status, disability, genetic information, military status, protected veteran status or any other factor protected by applicable federal, state or local laws.