Omnidian

Omnidian

Omnidian ensures the performance and protection of residential and commercial solar systems with a cash-back guarantee and proactive monitoring.

Renewable Electricity
51-250
Founded 2015
$24M raised

Description

  • Develop machine learning models to detect underperformance, faults, and anomalies in PV and storage time-series data.
  • Build diagnostic logic to identify root causes of asset underperformance.
  • Own the data science lifecycle from problem definition through development, validation, monitoring, and production deployment.
  • Partner with engineering to integrate models into Resolv and turn outputs into prioritized dispatch recommendations.
  • Work with operations to measure field impact and improve model performance over time.
  • Shape the technical roadmap for detection and diagnostics modeling.
  • Prototype new modeling approaches and validate their business impact before production investment.
  • Stay current on machine learning and energy analytics advances and share insights with the team.
  • Collaborate across product management, engineering, operations, and customers to scope and explain data science solutions.

Requirements

  • MS in a quantitative field or equivalent experience.
  • 6+ years of applied data science experience.
  • Strong hands-on experience with time-series methods, including anomaly detection, forecasting, seasonal decomposition, and state-space models.
  • Production ML experience, including deployment, monitoring, and retraining pipelines.
  • Proficiency in Python, including pandas, numpy, and scikit-learn, plus SQL.
  • Experience with at least one deep learning framework such as PyTorch or TensorFlow.
  • Experience working with noisy, irregularly sampled, multi-sensor data at scale.
  • Track record of leading modeling projects end to end and shipping them to production.
  • Strong written and verbal communication skills and ability to work with large cross-functional teams.
  • Experience mentoring data scientists or engineers and making architecture/tooling decisions for production ML systems on a major cloud platform (AWS, Azure, or GCP).
  • Experience with Claude Code or LLMs in operational workflows is a plus.
  • Familiarity with PV modeling tools such as pvlib or PVsyst, or with inverter, SCADA, or industrial IoT data streams is a plus.
  • Experience with Databricks, MLflow, or similar ML platform tooling is a plus.
  • Experience with probabilistic forecasting, failure prediction, ranking, prioritization, or decision optimization is a plus.
  • Ability to start in early Fall 2026 and no current or future sponsorship requirement.

Benefits

  • Competitive total compensation package with monthly health insurance premiums, bonuses, and long-term stock options.
  • Family medical, dental, vision, and disability coverage.
  • 401(k) administration with a $1,000 annual match.
  • Thoughtful paid time off.
  • 12 weeks of paid parental leave after 1 year for all FTE employees.
  • Four-week paid sabbatical after four years.
  • Remote work opportunities, with a Seattle office space available in Smith Tower.
  • Mentorship, career growth, and internal advancement opportunities.

Interested in this position?

Apply directly on the company website

Apply Now

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