Senior Fraud Analyst
Smartnumbers
full-time
Posted on:
Location: 🇬🇧 United Kingdom
Visit company websiteSalary
💰 £75,000 per year
Job Level
Senior
Tech Stack
CloudPythonSQLTableau
About the role
- Senior Fraud Analyst to join the Product & Success - Analytics team, reporting to the Chief Product & Success Officer.
- Use Smartnumbers solutions to support delivery of value to customers and investigate suspicious events.
- Collaborate with customers throughout the relationship lifecycle and act as their champion within the organisation.
- Articulate measurable value to customers aligned with industry and regulatory metrics.
- Operate on the Smartnumbers platform supporting organisations across financial services, telecommunications, and others.
- Hands-on, customer-facing and multi-team-focused role influencing product roadmap and industry perspectives.
- Analytics responsibilities: monitor, analyse, interpret fraud patterns; monitor industry trends; generate insights; develop KPIs; perform strategic reviews; support automation of analytics.
- Customer engagement: present findings to customers; create compelling narratives; participate in industry forums; support adoption of new capabilities.
- Cross-team collaboration: support sales and marketing reports; provide insights to Product team from customer feedback and analysis.
Requirements
- Curious - You want to understand the problems our customers face and how we might solve them.
- Eye for detail and drive to understand complex business logic and standardise processes.
- Experience developing and implementing fraud detection rules utilising machine learning and anomaly detection.
- Customer-centric - start with the customer and work back while understanding business constraints.
- Clear communicator capable of explaining things to diverse audiences.
- Natural ability to collaborate across teams and communicate complex findings.
- Proven track record of defining and championing outcome-based metrics that drive customer success.
- Comprehensive experience working with data in a product environment, particularly in authentication, fraud or risk analytics.
- Strong technical foundation in SQL and Python/R, with ability to wrangle complex datasets.
- Experience with modern data visualisation tools (Looker, Tableau, Power BI).
- Bachelor's degree or relevant qualifications in a quantitative field (Data Analytics, Statistics, Computer Science, or similar).
- Enthusiasm for rapid experimentation and a data-driven approach.
- Understanding of Agile methodologies and how they apply to data analytics.
- This isn’t a checklist; strong desire to learn fast, get stuck, and deliver value is essential.