PV Performance Data Analyst

EQUANS
royaume-uni
5 days ago
Create job alert

Company Overview

Leveraging decades of experience, Equans Solar & Storage is the one-stop partner for scaled, integrated and performant solutions on solar & storage energy projects.

Our mission: serving energy transition and low carbon world by empowering the deployment and integration of solar and storage solutions.

We provide solar PV & hybrid plants, energy storage, innovation and solar PV B2B customers.

Operating in 15 countries, with more than 1, experts dedicated to solar PV and high voltage, Equans Solar & Storage has installed over 6GW solar energy capacity worldwide, MWh BESS and is operating and maintaining approximately 2GW of solar PV plants.

Position Overview

We are seeking a highly analytical and detail-oriented PV Performance Data Analyst to support the operation and optimization of our growing portfolio of utility-scale solar power plants. The ideal candidate will leverage date analytics to assess plant performance, identify inefficiencies, and help drive strategic improvements across a portfolio of solar asset. 

Key Responsibilities 

Monitor and analyze real-time and historical data from SCADA, hypervisor and other monitoring systems across our global solar O&M portfolio. Includes collection, triage and analysis of data from sites as well as maintenance operations, requiring regular collaboration with site teams and/or O&M managers. Develop and maintain performance dashboards, reports, and KPIs for internal and external stakeholders. Comparison of actual performance data with forecasts (availability, Performance Ratio, Yield, EPI) in particular. Perform root cause analysis of underperformance issues (e.g., inverter faults, soiling, weather impacts, grid limitation, equipment degradation). Collaborate with O&M and engineering teams to implement data-driven performance improvement initiatives. Be an ambassador of PV performance across the business unit. Identify anomalies and develop automated alerting systems to flag operational issues. Develop of in-house tools for data analytics that can be used across a diverse portfolio of assets. Assist with data cleaning, integrity checks, and sensor calibration validations. Provide insights during the commissioning phase to validate expected vs. actual performance and support the acceptance tests. Coordinates the onboarding of newly connected plants to our hypervisor in the agreed timeline. Keep abreast of technological and commercial market developments and to inform senior management of any salient information.

Qualifications & Skills

Bachelor's degree in Data Science, Engineering, Renewable Energy, Physics, or a related field. 3+ years of experience in energy data anlytics, or a related role.  Proficiency in Microsoft Excel. Experience in analysis of time series, knowledge of visualizzation tools like Power BI and Python programming is considered an asset.  Knowledge of PV systems / electrical equipment. Experience with SCADA systems is considered an asset. Familiarity with databases and big data management. Able to work independently on MySQL, API and capacity for ETL process on large datasets.  Familiarity with CAD files and experience on design or schematics of solar farms (layouts, electrical diagrams, etc.), understanding of PV design concepts and flobal vision on construction & exploitation of projects. Knowledge of PVSyst is considered an asset. Organizational skills, reporting skills, attention to detail and good written and spoken communication skills. Team player, solution-oriented. Fluent in English. Knowledge of French and/or Spanish are considered a plus.

To learn more about us visit the . 

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!