Enterprise Account Manager

Ravelin
London
11 months ago
Applications closed

Related Jobs

View all jobs

Technical Solutions Engineer – Deep-Tech AI (RetailTech / Computer Vision)

Technical Solutions Engineer – Deep-Tech AI (RetailTech / Computer Vision)

Infosys - Senior Practice Lead- Data Science - London, UK

Infosys - Senior Practice Lead- Data Science - London, UK

Data Analyst - Fintech SaaS Game Changer. Hybrid

Data Science Apprentice - Enterprise Systems (Level 6)

Who Are We?

Hi! We are Ravelin!


We're a fraud detection company using advanced machine learning and network analysis technology to solve big problems. Our goal is to make online transactions safer and help our clients feel confident serving their customers.

And we have fun in the meantime! We are a friendly bunch and pride ourselves in having a strong culture and adhering to our values of integrity, thoughtfulness, resourcefulness and ambition. We really value work/life balance and we embrace a flat hierarchy structure company-wide.

Join us and you’ll learn fast about cutting-edge tech and work with some of the brightest and nicest people around -check out our Glassdoor reviews.

If this sounds like a great fit for you, we’d love to hear from you!

For more information check out ourblogto see if you would like to help us prevent crime and protect the world's biggest online businesses.

The Role

As an Account Manager, you will:

  • Develop and maintain positive long-term relationships with our merchant partners.
  • Proactively identify and manage new opportunities for clients.
  • Understand complex problems and communicate solutions in a clear, concise, and persuasive manner.
  • Be the key relationship partner with senior stakeholders.
  • Stay informed about all stakeholders within the business.
  • Work proactively, supported by a wider technical client support and investigations team.

Profile

You are:

  • Product minded and capable of learning complex information and communicating that knowledge to others.
  • A strong analytical thinker who thrives in a fast-paced, dynamic environment.
  • Equipped with a combination of business and technical knowledge to engage effectively with senior-level client contacts.
  • Bold and persuasive in your communication and presentation skills.
  • Passionate about using technology to solve business problems.
  • Proactive and able to manage your own workload and diary for the benefit of clients and colleagues.

Requirements

  • Understanding of Payments or Fraud 
  • Account management experience.
  • Ability to manage multiple projects and relationships simultaneously.
  • Experience in proactively growing client relationships within an account.
  • Experience in identifying, developing, negotiating, and closing deals.
  • Proven ability to influence others and lead client engagements.
  • Strong negotiation skills.
  • Highly skilled communicator.
  • Strong verbal and written presentation skills.
  • French or German language skills would be preferable

Benefits

  • Flexible Working Hours & Remote-First Environment— Work when and where you’re most productive, with flexibility and support.
  • Comprehensive BUPA Health Insurance— Stay covered with top-tier medical care for your peace of mind
  • £1,000 Annual Wellness and Learning Budget— Prioritise your health, well-being and learning needs with funds for fitness, mental health, and more.
  • Monthly Wellbeing and Learning Day— Take every last Friday of the month off to recharge or learn something new, up to you.
  • 25 Days Holiday + Bank Holidays + 1 Extra Cultural Day— Enjoy generous time off to rest, travel, or celebrate what matters to you.
  • Mental Health Support via Spill— Access professional mental health services when you need them.
  • Aviva Pension Scheme— Plan for the future with our pension program.
  • Ravelin Gives Back— Join monthly charitable donations and volunteer opportunities to make a positive impact.
  • Fortnightly Randomised Team Lunches— Connect with teammates from across the company over in person or remote lunches every other week.
  • Cycle-to-Work Scheme— Save on commuting costs while staying active.
  • BorrowMyDoggy Access— Love dogs? Spend time with a furry friend through this unique perk.
  • Weekly Board Game Nights & Social Budget— Unwind with weekly board games or plan your own socials, supported by a company budget.

*Job offers may be withdrawn if candidates do not meet our pre-employment checks: unspent criminal convictions, employment verification, and right to work.*





Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.