About Omnidian
Omnidian, Inc. is a fast-growing Series C tech-enabled service company revolutionizing performance assurance for the distributed solar and energy storage industries. Omnidian is building a more sustainable future for the planet through our passionate teams, our innovative technology, and by creating an amazing customer experience. We are a certified B Corp, headquartered in Seattle, WA
The Job
We are seeking a Senior Data Scientist to design, build, and scale advanced detection and diagnostic models for solar and storage assets. In direct support of Omnidian’s mission, your work will enable faster detection, fewer truck rolls, and better customer experience. As a key member of the data science team, you will report to the Director of Data Science and partner closely across product management, engineering, and operations to take models from idea to production in Omnidian’s Resolv platform.
What You'll Do
At Omnidian we believe in trust and autonomy. How you create an impact is ultimately up to you. Here is an outline of some of the things you’ll be doing:
Lead Issue Detection & Diagnostic Models (60%)
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 to Deploy High-Impact Models (20%)
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
Ideate and Explore New Models (20%)
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
Who You Are
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.
Experience You’ll Need
MS in a quantitative field or equivalent experience; 6+ years in applied data science
Strong hands-on experience with time-series methods: anomaly detection, forecasting, seasonal decomposition, state-space models
Production ML experience including model deployment, monitoring, and retraining pipelines
Proficiency in Python (pandas, numpy, scikit-learn) and SQL; experience with at least one of PyTorch/TensorFlow
Experience working with noisy, irregularly sampled, multi-sensor data at scale
Track record of leading modeling projects end-to-end — translating ambiguous business problems into measurable model outputs and shipping them to production
Proven written and verbal communication skills
The ability to work with large cross-functional team.
Experience mentoring data scientists or engineers and raising team standards
Experience with architecture and tooling decisions for production ML systems on a major cloud platform (e.g., AWS, Azure, GC)
Experience That’s a Plus
GenAI: Experience developing with Claude Code or putting LLMs into operational workflows
Solar Modeling: Familiarity with PV performance modeling tools (e.g., pvlib, PVsyst) or irradiance and weather datasets. Hands-on work with inverter, SCADA, or other industrial IoT data streams
Tooling: Experience with Databricks, MLflow, or similar ML platform and orchestration tooling
Forecasting: Experience with probabilistic forecasting or failure prediction — e.g., forecasting energy production, predicting part failure, or estimating remaining life
Optimization: Experience with ranking, prioritization, or decision-optimization problems such as alert triage or field-dispatch scheduling
Logistics
We plan to have this role start in early Fall 2026
We are unable to provide sponsorship for this role, now or in the future
Most of our roles offer the opportunity to work remotely
If you are in the Seattle area, we offer a vibrant office space in the historic and beautiful Smith Tower, in the heart of Pioneer Square
We prioritize applicants near one of our employee clusters and offer one or more local gatherings per year
Work-Life & Culture
We provide outstanding benefits including family medical, dental, vision, disability, 401(k) administration and $1k match per year and thoughtful paid time off
We offer 12 weeks of paid parental leave to all FTE employees (birthing and non-birthing) after 1 year, and four-week paid sabbatical leave after four years
We offer a competitive total compensation package that includes monthly health insurance premiums, bonuses and long-term stock options for every employee
We love to lift each other up through company-wide slack channels such as #puppiesandpets, #omnidian-wellness, #praiseandbooms and #sustainablefuture
We have affinity groups to help employees feel seen and supported, such as Rainbow Array, Black Lights Matter, Neurospicy R Us, Puente and more.
We are a passionate, mission driven team that believes in collaboration, mutual respect and trust. For examples, come Discover our Story!
Grow with Us
We mentor and invest in our employees and prioritize them for future opportunities. Check out our Instagram reels to see a few career journey examples, or this Omnidian Career Experience overview on YouTube.
Internal candidates: Check out our advice on Internal Transfer: Job Application Process
Here are the roles in this career track:
Senior Data Scientist
Staff Data Scientist
Principal Data Scientist
We’re a fast-growing growth company, which means we’re constantly reinventing processes, adding new products, and asking people to use all of their skills and talents. That means there’s going to be a lot of opportunities for you to grow, which also means you will likely be stretched in ways you’ve never experienced in a job before. If you are resilient, determined, and not afraid of a big challenge, come apply.
#LI-REMOTE
Privacy
Diversity and Inclusion
We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our customers. We are committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. We value diversity and inclusion and are committed to ensuring our hiring and retention practices, as well as our office culture, reflects this value.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
Omnidian is an equal opportunity employer. We are committed to diversity in the workplace. We make employment decisions on the basis of merit and business need. We hire without consideration to age, ancestry, citizenship, disability, gender expression, gender identity, marital status, national origin, political activity or affiliation, race, religion, sexual orientation, veteran status, or any other basis protected by law.
We invite you to be part of our mission to create a workplace that is inclusive and welcoming to all.
