Senior Sustainability & Commercial Data Analyst

Michael Page Technology
Exeter
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Operational Data Analyst

Senior EV Data Analyst

Data Analyst (Project Controls)

Managing Consultant - AI Business Solution Lead

Data Scientist

Senior Account Director London, England, United Kingdom

Leading Renewable Energy Provider require a highly motivated and detail-oriented Senior Sustainability & Commercial Data Analyst to join their team in the energy sector. The successful candidate will play a crucial role in supporting their sustainability initiatives and Commercial reporting by managing and analysing data related to Regulatory and weekly KPI reporting.

Client Details

Leading Renewable Energy Provider

Description

Leading Renewable Energy Provider require a highly motivated and detail-oriented Senior Sustainability & Commercial Data Analyst to join their team in the energy sector. The successful candidate will play a crucial role in supporting their sustainability initiatives and Commercial reporting by managing and analysing data related to Regulatory and weekly KPI reporting. This position requires a strong analytical mindset, proficiency in data management tools, and a passion for sustainability.

Key Responsibilities:

Data Collection and Management: Gather, clean, and maintain sustainability data from various sources. Ensure data accuracy and integrity for Regulatory reporting and internal KPI tracking. Regulatory Reporting: Prepare and submit regular reports to the Regulator, ensuring compliance with regulatory requirements. Monitor changes in regulations and update reporting processes accordingly. KPI Reporting: Develop and maintain weekly KPI dashboards to track sustainability performance. Analyse trends and provide insights to support decision-making. Data Analysis: Perform detailed data analysis to identify opportunities for improving sustainability performance. Generate reports and visualizations in Power BI to communicate findings to stakeholders. Collaboration: Work closely with cross-functional teams to gather data and implement sustainability initiatives. Support the Head of Finance & Sustainability in developing and executing sustainability strategies.

Key Skills & Experience:

Bachelor's degree in Sustainability, Environmental Science, Data Science, or a related field. Proven experience in data analysis, working with complex data from a variety of sources Experience with data visualization tools, ideally Power BI or similar Familiarity with regulatory reporting requirements and sustainability metrics (desirable but not essential) Proficiency in data analysis tools (eg, Excel, SQL, Python, R). Strong analytical and problem-solving skills. Excellent communication and presentation skills. Ability to work independently and as part of a team.

Profile

Bachelor's degree in Sustainability, Environmental Science, Data Science, or a related field. Proven experience in data analysis, working with complex data from a variety of sources Experience with data visualization tools, ideally Power BI or similar Familiarity with regulatory reporting requirements and sustainability metrics (desirable but not essential) Proficiency in data analysis tools (eg, Excel, SQL, Python, R). Strong analytical and problem-solving skills. Excellent communication and presentation skills. Ability to work independently and as part of a team.

Job Offer

Opportunity to deliver enhanced analytics capability
Opportunity to join a rapidly expanding Renewable Energy company

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.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.

Career Paths in Machine Learning: From Entry-Level Roles to Leadership and Beyond

Machine learning has rapidly transformed from an academic pursuit to a cornerstone of modern technology, fueling innovations in healthcare, finance, retail, cybersecurity, and virtually every industry imaginable. From predictive analytics and computer vision to deep learning models that power personalisation algorithms, machine learning (ML) is reshaping business strategies and creating new economic opportunities. As demand for ML expertise continues to outstrip supply, the UK has become a vibrant hub for machine learning research, entrepreneurship, and corporate adoption. Whether you’re just starting out or have experience in data science, software development, or adjacent fields, there has never been a better time to pursue a career in machine learning. In this article, we will explore: The growing importance of machine learning in the UK Entry-level roles that can kick-start your ML career The skills and qualifications you’ll need to succeed Mid-level and advanced positions, including leadership tracks Tips for job seekers on www.machinelearningjobs.co.uk By the end, you’ll have a clear view of how to build, grow, and lead in one of the most exciting fields in modern technology.