Solar Performance & Analytics Engineer

Univers is hiring a Solar Performance & Analytics Engineer to enhance Bazefield Solar AI Analytics, focusing on optimizing solar asset performance. The role involves analyzing operational data, developing machine learning models, and designing data pipelines. Candidates should be near office locations in Porsgrunn, Norway; Nantes, France; or Philadelphia, USA. This position combines research and development with practical applications in the renewable energy sector.
The company:

Univers Bazefield is the world-leading provider of the Bazefield Operation Management System, specializing in the renewable energy market. We develop, sell, and deliver Bazefield as a SaaS (Software as a Service) platform or as an on-premises solution. The renewable energy sector is rapidly expanding and highly competitive and encompasses wind, solar, storage (BESS), hydro, and hybrid energy systems. This market includes both established, large-scale energy companies and new entrants. Our customers use Bazefield to monitor, analyse, and optimize their energy assets.

Univers provides the world’s most comprehensive decarbonization system. 

We help companies and countries optimize energy systems and reduce carbon emissions with accurate, reliable, and actionable decarbonization data. Our EnOS (Energy and Environment Operating System) platform connects on-the-ground operational technology and in-the-cloud intelligence to deliver real-time energy data and data-driven carbon monitoring, reporting, and abatement.

With 220 million sensors and smart devices connected, 550GW of renewable energy under management, and a community of over 500 customers, we’re helping the world’s leading businesses get the world to net zero—and what comes after it.

The challenge is immense, but so are the rewards. Join our team and help move the planet towards sustainability. For more information, please visit https://univers.com

Univers Bazefield expands its team in Europe/US:

Role: Solar Performance & Analytics Engineer

We are hiring a Solar Performance & Analytics Engineer located near any of our office locations (Porsgrunn, Norway or Nantes, France or Philadelphia, USA):

As a Solar Performance & Analytics Engineer, you will contribute to the continuous development and enhancement of Bazefield Solar AI Analytics, a product that delivers automated, data-driven recommended actions to O&M and asset managers to boost PV performance and maximize revenue.

This position offers a unique opportunity to operate at the intersection of research and development (R&D) and real-world operational impact, combining cutting-edge innovation with hands-on problem-solving across global solar portfolios.

You will join a team of solar scientists and product engineers, working closely with energy experts, software engineers, and client-facing teams to build solutions that optimize solar asset performance, reduce downtime, and streamline O&M processes. If you are passionate about renewable energy and advanced data workflows, this is your chance to make a measurable impact.

Your job scope will include, but not limited to:

1. Analyse SCADA, inverter, tracker, weather operational data, and more, to detect anomalies, assess performance, and generate actionable insights for O&M optimization.
2. Develop innovative ML models and hybrid physics-AI digital twins for advanced maintenance, fault detection, and power forecasting, among many other workstreams.
3. Write clean, well-documented, and efficient code following best practices to ensure high performance, maintainability, and scalability across data and application layers.
4. Design and deploy robust data pipelines with Git-based version control, automated CI/CD workflows, and thorough unit and integration testing to ensure reliable, scalable, and reproducible analytics in production environments.
5. Collaborate with engineering, software, and asset management teams to design on-premises and cloud-based decision support tools and improve platform intelligence.
6. Write clear and structured product requirements based on client feedback or requests, covering the full stack from raw data processing to frontend/UI presentation.
7. Integrate and utilize AI tools (e.g., ChatGPT, Copilot, LangChain) to automate reporting, accelerate debugging, and improve development workflows.
8. Produce clear and validated technical documentation, including internal reports, scientific articles, and whitepapers, to support decision-makers, clients, and internal development.

Ideal Candidate Profile:

You bring technical excellence and operational know-how. We are looking for someone with the following qualifications and mindset:
- Master’s or PhD in Engineering, Computer Science, Data Science, or a related technical field.
- Strong programming skills in Python and experience with time series analysis, statistics, and machine learning (scikit-learn, pandas, NumPy, etc.), familiar with tools like ruff, pydantic, and respecting clean code standards.
- Deep experience with SCADA systems and platforms (ideally Bazefield platform), operational data, and performance KPIs in solar PV plants, are very welcomed

- Good understanding of digital twins, predictive maintenance models, and PV plant performance optimization methods
- Previous experience in solar asset management or O&M operations is highly appreciated, especially with direct exposure to performance workflows.
- Experience working with Linux environments, Docker containers, and Git-based version control are very welcome, but not mandatory.
- Proficiency using AI-based tools for workflow acceleration, code generation, and technical writing.
- Excellent communication skills and the ability to work effectively across multinational teams and with external partners.
- Proactive, self-driven problem-solver with strong initiative and technical judgment.

Univers is an Equal Opportunity Employer. Employment decisions are made without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other characteristics protected by law.