Moneyhub

Customer Success Manager

• Keep in touch with clients through meetings and ticket reviews to make sure they are happy and getting the most out of Moneyhub’s software.
• Use 1st and 2nd line support skills to solve issues fast, leveraging knowledge of tooling for better client experience and ticket management.
• Join process improvement efforts and take ownership of tasks to support the company’s Objectives and Key Results (OKRs).
• Developed a good understanding of company products, client needs, and important software like Zendesk and JIRA.
• Set up clear communication with clients and internal teams.
• Managed initial client support questions with help and began working on ticket resolution.
• Manages client accounts on their own, holding regular meetings and keeping satisfaction high.
• Able to recognise commercial opportunities (up sell) with clients and share that with Moneyhub sales and account managers.
• Handles 1st and 2nd line support issues well, using Zendesk and JIRA effectively.
• Acts as a reliable advisor to clients, providing solutions that fit their needs even under pressure.

Customer Success Specialist

Machine Learning Engineer

• As a Machine Learning Engineer at Moneyhub, you'll bridge the gap between data science and software engineering. You'll be responsible for developing production-ready data solutions that solve real user problems—focusing on delivering working code rather than just analysis or prototypes.
• What You'll Work On:
• - Data Enrichment Systems: Build and maintain systems that enhance raw financial data, including our transaction categorisation engine that underpins budgeting capabilities and affordability checking services
• - Production-Ready Solutions: Transform data science concepts into robust, high-performance code that can handle our production workloads
• - Pragmatic Algorithm Development: Create and optimize algorithms using the most appropriate techniques to solve specific user problems
• - Data-Driven Product Innovation: Collaborate with product teams to translate business requirements into technical solutions that enrich financial data
• - User Insights: Analyze user characteristics and segmentation to support business decisions and product development