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- Tasks: Analyse and manage data to support revenue recognition and financial reporting.
- Company: Professional membership organisation with a focus on finance and analytics.
- Benefits: Flexible contract role with opportunities for skill development and networking.
- Why this job: Join a dynamic team and make an impact on financial accuracy and reporting.
- Qualifications: 1-3 years in finance or analytics, strong data management skills required.
- Other info: Great opportunity for growth and learning in a supportive environment.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking an Interim Revenue & Data Analyst to provide contract support within the Finance team of a professional membership organisation. The successful candidate will work extensively with NetSuite and Excel, supporting data management, validation, and reporting activities that underpin accurate revenue recognition and financial close. This role is well suited to someone who is highly analytical, detail‑oriented, and confident working with large datasets.
Key Responsibilities
- Perform detailed data management and validation within NetSuite and Excel.
- Support the application and understanding of revenue recognition rules and policies.
- Review revenue‑related data inputs across the different revenue performance obligations (exam registrations, exam sitting dates, deferrals, upsells etc.).
- Support both front‑end review (source data review, consistency) and back‑end review testing (output calculation, allocations, recognition periods).
- Maintain and update Excel‑based revenue trackers and supporting schedules.
- Identify data inconsistencies and escalate issues with clear supporting analysis.
- Support reconciliation projects, ensuring revenue and deferred revenue balances are accurate and complete.
- Support month‑end and fiscal close processes through data preparation and validation.
- Assist with audit preparedness, particularly in advance of fiscal year‑end (August), by preparing schedules and supporting documentation.
- Continue supporting front‑end and back‑end review testing as required.
Skills and Experience
- Proven ability to work confidently with large datasets.
- 1–3 years’ experience in a finance, accounting, or analytical role.
- Confident working independently with data, while escalating issues appropriately.
- Strong organisational skills and ability to manage detailed, repetitive tasks.
- Clear communicator, able to explain data findings to senior team members.
- Willingness to learn and apply revenue recognition concepts.
- Experience working with NetSuite or a similar ERP system.
- Exposure to revenue, billing, deferred revenue, or reconciliation work.
- Prior experience supporting month‑end close or audit processes.
Interim Data Analyst (Revenue) in London employer: Brewer Morris
Contact Detail:
Brewer Morris Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Interim Data Analyst (Revenue) in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the finance and data analysis fields. You never know who might have a lead on an interim role or can put in a good word for you.
✨Tip Number 2
Get your hands dirty with data! If you can, practice using NetSuite or Excel with real datasets. This will not only boost your confidence but also give you some solid examples to discuss during interviews.
✨Tip Number 3
Prepare for those tricky interview questions! Brush up on revenue recognition rules and be ready to explain how you've handled data inconsistencies in the past. We want to see that analytical mindset in action!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Interim Data Analyst (Revenue) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Interim Data Analyst role. Highlight your experience with data management, especially in NetSuite and Excel, and showcase any relevant projects that demonstrate your analytical skills.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this role. Mention your familiarity with revenue recognition rules and how your previous roles have prepared you for the responsibilities outlined in the job description.
Showcase Your Analytical Skills: In your application, don’t shy away from sharing specific examples of how you've worked with large datasets. We want to see your problem-solving abilities and how you've tackled data inconsistencies in the past.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role without any hiccups!
How to prepare for a job interview at Brewer Morris
✨Know Your Numbers
Make sure you brush up on your data management skills, especially with Excel and NetSuite. Be ready to discuss how you've handled large datasets in the past, and prepare examples of how you've validated and reconciled data. This will show that you're not just familiar with the tools, but that you can use them effectively.
✨Understand Revenue Recognition
Familiarise yourself with revenue recognition rules and policies before the interview. Being able to explain these concepts clearly will demonstrate your analytical skills and your readiness to tackle the responsibilities of the role. Think of scenarios where you've applied these principles in previous roles.
✨Prepare for Practical Questions
Expect questions that require you to think critically about data inconsistencies or reconciliation challenges. Prepare to walk through your thought process on how you would approach these issues. This will highlight your problem-solving abilities and attention to detail.
✨Communicate Clearly
Practice explaining complex data findings in simple terms. You might be asked to present your analysis to senior team members, so being a clear communicator is key. Use examples from your past experiences where you successfully conveyed important information to non-technical stakeholders.
