Contract type: Permanent
Hours: 37.5
Salary: circa £45,000 depending on experience
Location: Canary Wharf
WFH policy: Employees are required to attend the office 2 days/week
Flexible working: Variety of flexible work patterns subject to line manager discretion e.g. Compressed 9-day fortnight.
Reports to: Energy Analytics Manager
Deadline Note: We reserve the right to close the advert before the advertised deadline if there are a high volume of applications.
Role Summary:
Energy Analysts have a diverse technical skill set, with particular emphasis on energy market analysis and policy expertise. Energy Analyst roles sit across a number of functions within the Analytics team, including Forecasting Operations, New and Existing Scheme Insights, and Business Support where, as embedded analysts, they support other teams across LCCC.
Depending on the destination role, the postholder may own, develop and improve core forecasting systems and critical processes including automation, bug-fixing and assurance. Analysts enable and drive levy setting through robust pre-analysis, recommendations and clear options, directly support other internal teams with analytical deep-dives and modelling required throughout the year, producing data insights that inform scheme delivery, organisational decisions and government policy.
The ideal candidate will have an understanding of energy market fundamentals or be able to demonstrate the ability and willingness to quickly develop expert knowledge in a new domain. They will be able to demonstrate a high level of analytical competence, and will be driven by curiosity and seek to continuously improve themselves by developing new skills and approaches to solve problems. The ideal candidate will be required to take on complex challenges with a sense of urgency and enthusiasm, developing and communicating data insights in a clear and succinct way. Furthermore, the candidate will be adaptable and inquisitive, with a strong willingness to develop and improve existing processes for example by applying AI and automation techniques.
Forecasting & Modelling
- Own, develop and improve core forecasting systems and critical processes such as ELFO, including automation, bug-fixing and assurance.
- Maintain and develop forecasting models.
- Continuously improve forecasting tools and processes, proposing practical changes that improve quality, resilience and efficiency.
- Enable and drive levy setting through pre-analysis, evidence-based recommendations and clear options for decisions and actions.
Performance Analysis & Insight
- Investigate and produce recommendations on variances between forecast and out-turns.
- Assist with reporting and interpretation of KPIs and performance metrics.
- Communicate key findings and actionable recommendations.
Data, Market & Policy Intelligence
- Review and collate industry-wide data sources.
- Monitor and synthesise policy developments and energy market changes.
- Set analytical standards through communities of practice, style guides, standardised models and design principles.
Stakeholder Engagement & Leadership
- Own relationships with internal teams.
- Chair meetings with senior stakeholders (e.g. CFO) to secure sign-off on key deliverables.
- Drive alignment and decision-making through clear communication.
Essential:
- A good first degree or higher in a highly numerate subject or equivalent experience is essential, such as Engineering, Data Science, Computer Science, Economics, Statistics, Mathematics, Operational Research and other quantitative STEM subjects
- AND/OR proven experience with forecasting or predictive analysis.
- The ability to communicate clearly and concisely in person and through written output to both technical and non-technical audiences. Including presenting and giving teach-ins on analytical work.
- Highly analytical and strong critical thinker.
- Experience using Python, R or other coding language to conduct analysis.
- Experience with version control software such as Git.
- Experience using Excel to conduct analysis.
- Experience with data visualisation.
- Experience with writing documentation or tutorials, developing, testing, quality assuring and maintaining models.
- An interest in the energy sector and a passion for renewable energy technology, improving energy security and helping the government achieve Net Zero.
Desirable:
- Experience in the energy sector.
- Experience with PowerBI or equivalent.
- Experience with SQL.
- Interest or experience using AI and automation to optimise processes and deliver results.
As if contributing to and supporting work that makes life better for millions wasn’t rewarding enough, we offer a full range of benefits too. Key benefits that may be available depending on the role include:
- Annual performance based bonus, up to 10%
- 25 days annual leave, plus eight bank holidays
- Up to 8% pension contribution
- Financial support and time off for study relevant to your role, plus a professional membership subscription
- Employee referral scheme (up to £1500), and colleague recognition scheme
- Family friendly policies, including enhanced maternity leave and shared parental leave
- Free, confidential employee assistance, including financial management, family care, mental health, and on-call GP service
- Three paid volunteering days a year
- Season ticket loan and cycle to work schemes
- Family savings on days out and English Heritage, gym discounts, cash back and discounts at selected retailers
- Employee resource groups
The Low Carbon Contracts Company (LCCC) exists to help decarbonise the generation of electricity and make it more affordable for the future. Our work is central to the delivery of the Government’s objective to achieve Net Zero target by 2050.
Discover more about LCCC and what it's like to work with us by watching this video:
https://vimeo.com/1071699533
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At LCCC, we are powered by curiosity, driven to learn from different perspectives and experiences as we work towards a flexible energy future. We are committed to fostering a diverse and inclusive workplace where everyone can be their authentic selves and feel empowered to own every outcome.
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