<p>Ravelin prevents fraud and protects margins for online businesses around the globe. </p><p>We look at our clients' data more thoroughly than anyone else to provide the most accurate fraud scores.…
<p>Ravelin prevents fraud and protects margins for online businesses around the globe. </p><p>We look at our clients' data more thoroughly than anyone else to provide the most accurate fraud scores.…
Product: AI-native fraud prevention for online merchants using machine learning, graph-link analysis, behavioral analysis, consortium data and rules
Founded / HQ: Founded 2014; headquartered in London
Scale (2023): Protects 300+ merchants and produced 10 billion fraud scores in 2023
Funding: Raised a $20M Series C (Jul 2020); total disclosed funding $39,200,000 USD
Exit: Acquired by Worldpay (announcement dated Feb 4, 2025)
Company Overview
Problem Domain
Online fraud detection and payments optimization for e-commerce and digital platforms
Founded
2014
Industry
Fraud prevention / Payments
Tech Stack
Machine learning
Graph-network link analysis
Behavioral analysis
Consortium data
Business rules
Real-time decisioning
Data science
Funding Track Record
Seed- Mar 12, 2015
Seed backing by Passion Capital (undisclosed amount)
Early round- Sep 29, 2015
>£1.3M
Institutional investors plus angel participants
Series A- Oct 18, 2016
£3M
Series B- Sep 11, 2018
£8M
Existing investors (Amadeus Capital Partners, Passion Capital, Playfair Capital) participated
Series C- Jul 15, 2020
$20M (¥16.4M equivalent noted)
Participation from existing investors including Amadeus Capital Partners, BlackFin Tech, Passion Capital
Investor Signal
“Backed by Draper Esprit, BlackFin Capital Partners, Amadeus Capital Partners, Passion Capital, Playfair Capital; later acquired by Worldpay (announcement dated Feb 4, 2025)”
Founders
What we do
Join the Team
Data Scientist
On-SiteLondon, GB
On-Site • London, GB
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Who you are
1 years' experience or training as a data analyst, intelligence analyst or data scientist
Strong critical thinking skills, intuitively curious and able to diagnose data issues
Strong communication and presentation skills
Diligence, attention to detail, ability to prioritise and follow through on tasks
Experience with SQL - ability to run complex queries to answer your own questions
Experience with Python for data analysis
Knowledge of supervised and unsupervised ML techniques
Desirable: some knowledge, understanding or experience of network analysis
Desirable: hands-on experience with DBT
What the job involves
Benefits
Remote first
Mental health support
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We are currently looking for a Junior level Data Scientist to join a fantastic team of client-facing data scientists and client support analysts
You will be working to discover patterns and trends concerning fraud in our clients' data
In this key role, you'll be applying exploratory analysis to form realistic and useful narratives from data, asking “why” as well as “what” and “how"
You will interact directly and indirectly with clients to help them understand what is happening with their fraud, and help us to target our efforts ever more precisely
Work directly with clients to provide fraud analytics and ML model insights
Analyse datasets with millions of rows to identify fraud patterns, trends and emerging threats to improve client performance
Discuss specific fraud problems with clients, in order to deeply understand how they manifest and to propose effective and elegant solutions
Prepare reports and present findings of analysis to clients when required
Identify new model features and improve model performance
Optimise the performance of our graph networks using network analysis
Get hands on experience with our cloud infrastructure and make the most of the available tools for enhancing our clients’ data and performance
Build internal tools in Python for optimising and improving our analytical capabilities
Charity "Gives Back" initiative
Volunteering opportunities
Flexible hours
Employer-contributed pension scheme
Equity scheme
Lunches twice a month (& the office kitchen is stocked with treats and goodies)
Home office budget
One day each quarter dedicated to learning and personal development
Individual yearly learning budget of £1000, and access to company wide training
Comprehensive medical cover through AXA or US equivalents, including dental and optical cash back
Remote fitness - virtual yoga twice a week, team HIIT sessions, and online Pilates class
