Senior Payment Analyst

Senior Payment Analyst

Full-Time 50000 - 90000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Analyse payment data to optimise transactions and improve revenue.
  • Company: Join Fanvue, a leading AI-powered creator monetisation platform.
  • Benefits: Competitive salary, autonomy, wellness perks, and a fast-paced environment.
  • Other info: Dynamic team culture with opportunities for growth and innovation.
  • Why this job: Make a real impact on the creator economy with your analytical skills.
  • Qualifications: Experience in high-risk payments and strong SQL skills required.

The predicted salary is between 50000 - 90000 £ per year.

Join us in redefining the creator economy with AIFanvue, one of the fastest-growing creator monetisation platforms globally. We're an AI-powered, creator-first platform helping creators connect, engage, and earn directly from their audiences at scale. Fanvue has surpassed £200M+ in annual recurring revenue, with triple-digit year-on-year growth, supporting hundreds of thousands of creators and millions of fans worldwide.

We process tens of millions of pounds per month across a multi-acquirer, multi-MID payments stack, and we need someone whose entire job is to interrogate the data, find what's broken, and fix it. This is an analytical operations role where your work has direct, measurable impact on revenue and margin every single month.

The Role

You will be the analytical engine behind Fanvue's payments function. You'll work directly with the CBOO to turn raw payments data into real decisions. Auth rates, decline patterns, routing logic, processing costs, reconciliation accuracy: you'll own all of it, continuously, not as a one-off project.

One focused week of payments optimisation drove a significant increase in transaction fee revenue. That gain is not being sustained or built on, because nobody owns it. You will.

What You'll Do

  • Diagnose and recover declined transactions by analysing decline codes, retry logic, and timing across acquirers.
  • Build and optimise intelligent routing rules based on card type, user behaviour, spend value, and platform activity.
  • Map per-transaction COGS across every processor, gateway, FX fee, scheme fee, refund, and chargeback, then reduce it.
  • Own daily reconciliation alongside Finance, identifying and closing gaps across multiple acquirer data formats.
  • Diagnose MIT/renewal auth failures and systematically improve renewal success rates.
  • Identify friction and drop-off in the payment journey and flag findings to Product and Engineering.
  • Build and maintain a live payments KPI dashboard covering auth rates, decline breakdowns, cost per transaction, chargeback ratios, and retry uplift.

Who You Are

  • Deep experience in high-risk payments (multi-acquirer setups). This is not "Stripe but with more chargebacks", the nuances of our environment are fundamental to the role.
  • SQL-proficient and self-sufficient. You pull your own queries, build your own views, and work directly in the data warehouse without waiting for anyone else.
  • Comfortable working with messy, inconsistent data from multiple acquirers: webhook responses, SFTP files, acquirer statements, spreadsheets with no schema. You don't need clean data handed to you.
  • Can form a hypothesis, run an experiment, read the outcome, and adjust, in a continuous loop. The core of this role is judgement-heavy, not process-heavy.
  • A communicator who can take complex data findings and translate them into clear recommendations for senior stakeholders without burying the point in caveats.
  • Self-starting on a clean sheet. You can build structure and cadence in a role without an existing playbook.
  • We care about judgement and analytical depth, not credentials.

You’ll Thrive Here If

  • You love living in data and finding the discrepancy between what you expected and what happened.
  • You want your analysis to have immediate, visible commercial impact.
  • You enjoy building from scratch rather than inheriting a playbook.
  • You're motivated by making things measurably better, not just reporting on them.

You’ll Struggle Here If

  • You need clean, structured datasets handed to you before you can work.
  • You're uncomfortable presenting findings and recommendations to senior stakeholders.
  • You prefer process-heavy environments with rigid frameworks.
  • You need close supervision to stay on track.

Why Join Fanvue

  • Competitive salary.
  • Ownership from day one.
  • Fast-moving team with real autonomy.
  • Direct line of sight to outcomes and visible impact.
  • AI-native working environment.
  • Access to gyms, studios, wellbeing partners, and premium wellbeing apps.
  • Recognised in the Sunday Times Best Places to Work, two years running.
  • Winner of an International Business award for fastest-growing company.

Fanvue is for Everyone

We believe diverse teams build better products, and if you are excited by the role but do not tick every box, we still encourage you to apply. We hire on potential, mindset, and what you will build, not just where you have been.

Senior Payment Analyst employer: Fanvue.com

Fanvue is an exceptional employer, recognised as one of the Sunday Times Best Places to Work for two consecutive years. With a vibrant and inclusive work culture, we offer remote-friendly opportunities across the UK and Europe, high annual leave flexibility, and a commitment to employee growth through upskilling support. Join us to be at the forefront of crypto fraud investigation in a rapidly expanding company that values innovation and diversity.

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Contact Details:

Fanvue.com Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Payment Analyst

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Apply Directly through Our Website

When you find a suitable opening like Senior Payment Analyst at Fanvue.com, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Payment Analyst

Analytical Skills
SQL Proficiency
Data Analysis
Payments Optimisation
Transaction Reconciliation
Problem-Solving Skills
Communication Skills

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Fanvue.com, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Fanvue.com. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Fanvue.com

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Fanvue.com!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.