We are seeking aSenior Data Scientist to design, build, and scale advanced detection and diagnostic models for solar and storage assets.
Key Responsibilities
Develop machine learning models that detect underperformance, faults, and anomalies in PV and storage system time-series data
Build diagnostic logic that distinguishes root causes (soiling, shading, inverter clipping, string outages, communication gaps, sensor drift, degradation) of underperformance.
Own the data science lifecycle from problem definition and model development through validation and monitoring, partnering with Engineering to deploy models into production.
Help shape the technical direction for the detection and diagnostics roadmap and strengthen the team’s approach to model design, validation, and testing
Partner with engineering to integrate your models into Resolv, turning model outputs into concrete, prioritized dispatch recommendations
Close the loop with operations: track how your recommendations perform in the field — truck rolls avoided, issues resolved faster — and use that data to improve your models
Explore and prototype new modeling approaches and validate their business impact before investing in production deployment
Stay current with advances in ML and energy analytics, and share what you learn with the team
Requirements
You own outcomes and measure success by the decisions your models improve
You are rigorous with messy, real-world data. You dig into the quality, provenance, and business context of the data your models consume
You take your models through the full lifecycle (from problem framing, prototyping, and validation to deployment and monitoring)
You translate across domains. You work fluently with engineers, operations teams, and customers to scope what data science can (and can't) solve, and you can explain a diagnostic model to someone who has never heard of state-space methods.
Ready to Apply?
Join Omnidian and make an impact in renewable energy