About this role
About Octopus Energy for Business
Octopus Energy for Business (OEB) is a rapidly scaling energy supplier with more than 130k business customers. We aim to accelerate the business sector’s transition to net zero whilst providing low-cost energy that meets the needs of our customers.
We’ve pioneered PPA-backed supply for mid-market businesses through Electric Match, led the way for SME smart tariffs with Shape Shifters and are the established market leader for enabling EV public charging through energy supply and services.
About the role
We’re seeking a highly skilled and data-driven Commercial Analytics Manager to modernise how we track and forecast our financial performance. In this role, you’ll take ownership of our business forecasting processes and lead the transition away from legacy, multi-tab spreadsheets. By leveraging modern data tools, you will build robust, automated pipelines to analyse margins, investigate variances, and provide actionable insights that optimise OEB's financial performance. You’ll collaborate closely with our Data team, finance teams, and senior leadership to ensure our financial strategies align with the company's sustainable growth objectives.
What you'll do
Provide consistent portfolio level reporting for OEB to determine overall net margins. This will include revenue, cost of sales, debt and operational expenditure.
Lead the development and management of the company’s forecast, ensuring accuracy and alignment with strategic goals.
Work with the team to interrogate the entire cost stack to influence pricing decisions.
Develop margin optimisation strategies, including pricing adjustments, cost reductions, and process improvements.
Improve accuracy of gross margin calculations in partnership with Finance and Pricing teams.
Lead meetings with colleagues and senior management to provide clear options in the decision making process.
Work closely with the pricing team to influence key decisions to ensure we provide customers with a wide range of tariffs which are set with a conscious view of outturned margins.
Provide monthly reporting packs to monitor different aspects of performance including budgets and variance analysis.
Work closely with business units to gather key inputs and assumptions for accurate forecasting.
Improve the tools behind our forecasting, moving away from spreadsheet-heavy processes towards Python and SQL-based analysis.
Compare forecasts with monthly actuals and thoroughly investigate variances across the business's book.
What you'll need
Strong proficiency in SQL to extract, manipulate, and transform complex commercial data.
Experience using Python for data analysis, automation, or financial modeling.
A minimum of 3 years experience of using data and coding to solve commercial, pricing, or financial problems.
A proven track record of untangling complex, legacy spreadsheet processes and replacing them with streamlined, automated solutions.
Strong financial acumen, particularly with reporting margins, forecasting, and variance analysis.
The ability to bridge the gap between commercial finance and data analytics, summarising complex findings into clear narratives for senior, non-technical stakeholders.
A self-starter mentality with the confidence to take ownership of a growing area, solve complex problems, and constantly introduce new processes.
Ideally, previous financial, commercial, or pricing experience within the energy industry (considered a strong bonus, though we are open to exceptional data-driven candidates from other sectors).