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
Role: Senior Engineering Data Scientist – Wind Turbine Health & Predictive Maintenance
Location: Nantes, Paris, Madrid or within travelling distance to a Univers office location.
Role Overview:
We are looking for a skilled professional with a solid technical background in wind turbine technology to join our fast-growing team focused on the digitalization of renewable energy and energy IoT at Bazefield Univers. This role is based in Nantes or Paris, with remote work options available.
As part of this team, you will collaborate closely with a global network of renewable energy experts and work cross-functionally with front-end and back-end software development teams. You will contribute to the creation of AI-driven software products, specializing in wind turbine analytics and component failure prediction. Additionally, you will engage with external stakeholders, supporting clients in solving complex analytics challenges and optimizing their renewable energy operations.
Responsibilities:
• Drive Product Development: Actively program and contribute to the product roadmap, implementing both physics-based and machine learning-based solutions. Develop new product ideas and enhancements to maintain innovation and competitiveness.
• Predictive Maintenance Models: Build predictive algorithms focused on assessing the health of critical wind turbine components, such as blades, gearboxes, bearings, and generators, with an emphasis on vibration signal processing.
• Product Management: Determine the most effective way to present analysis results to users, ensuring they drive actionable insights and maximize value. Interact with the software engineering team to implement your ideas
• Integration into Software Platforms: Work with software development teams to integrate diagnostic algorithms into real-time monitoring platforms. Ensure the system is scalable, user-friendly, and provides engineers with actionable information.
• Continuous Optimization: Enhance existing monitoring systems and develop new algorithms based on evolving wind turbine technology, changes in environmental conditions, and new data sources (e.g., drones, lidar).
• Collaborate Cross-Functionally: Work closely with internal teams—Go-to-Market, Presales, Solution Architects, and Software Development—as well as external stakeholders, including renewable asset owners, developers, and O&M companies, to drive project alignment and value.
• Serve as a Thought Leader: Represent the company as an industry expert by presenting at conferences and trade shows, publishing papers, and engaging in market-facing activities to drive product recognition and adoption.
Desired Skills and Experience:
• Master’s, or PhD in Mechanical Engineering, Electrical Engineering, or a related field. Specialization in wind energy is highly desirable.
• Strong understanding of vibration analysis techniques and engineering practices within the wind industry.
• Proficiency in Python following clean code practices, experiences in time series analysis, statistics and machine learning
• Strong background in wind turbine performance analysis and fault detection
• Experience in condition-based maintenance (CBM) and digital twin applications in wind energy preferred
• Experience working with finite element analysis (FEA) or computational fluid dynamics (CFD) in relation to turbine performance or component health preferred
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.