Machine Learning Engineer

Summary

Join Moneyhub as a Machine Learning Engineer and bridge the gap between data science and software engineering. You will build and maintain data enrichment systems, focusing on production-ready solutions and pragmatic algorithm development. Collaborate with product teams to translate business requirements into technical solutions. Analyze user characteristics to support business decisions. Moneyhub offers a flexible work environment with remote work options and various benefits. The ideal candidate possesses strong software engineering skills, experience with data processing, and excellent communication abilities.

Requirements

• 3+ years of experience in data science or related engineering roles
• Strong software engineering practices with proficiency in Python
• Working knowledge of Node.js for backend integration
• Experience building and deploying data solutions to production environments
• Practical knowledge of data processing techniques and relevant frameworks
• Understanding of when to apply ML algorithms vs. simpler approaches to solve problems
• Experience with statistical analysis and ability to interpret results to drive decision-making
• Proven ability to clean and prepare data for analysis and enrichment
• Excellent communication skills with ability to present technical concepts to non-technical stakeholders
• Bachelor's or Master's degree in a numerical or engineering subject (Data Science, Computer Science, Mathematics, or related field)

Responsibilities

• Develop production-ready data solutions that solve real user problems—focusing on delivering working code rather than just analysis or prototypes
• Build and maintain systems that enhance raw financial data, including our transaction categorisation engine that underpins budgeting capabilities and affordability checking services
• Transform data science concepts into robust, high-performance code that can handle our production workloads
• Create and optimize algorithms using the most appropriate techniques to solve specific user problems
• Collaborate with product teams to translate business requirements into technical solutions that enrich financial data
• Analyze user characteristics and segmentation to support business decisions and product development

Preferred Qualifications

• Experience with containerization using Docker
• Has worked on high-performance data processing systems
• Can perform data science analysis independently but focuses on production implementation
• Understands the difference between exploratory work in notebooks and production-ready code
• Experience optimizing algorithms for performance and scale
• Demonstrates a pragmatic approach to problem-solving, always seeking the simplest solution that delivers the best results
• Can evaluate when machine learning is appropriate and when simpler approaches would be more effective

Benefits

• 5% company contribution towards your Pension from your very first day with us
• 3% contribution from your self
• 25 days of holiday (plus bank hols), rising to 30 days after two years
• Choose to take your entitlement to UK bank holidays at other times based on your own days of significance
• Private medical insurance, including cover for pre-existing conditions, plus dental and optical benefit
• 3 Months Moneyhubber Family Pay when you become a new parent
• Permanent health insurance and life cover - much greater than the industry standard (death in service)
• Employee assistance programme
• Professional development support, with dedicated allowance of time and money
• Life event leave
• Cycle to work scheme
• EV Car Scheme
• ��750 towards professional memberships
• Remote working benefits, including work from almost anywhere, access to co-working spaces and support for your home office set-up
• High spec laptop
• Holiday purchase