Machine Learning Engineer
Machine Learning, Data Science, MLOps, Software Development, Python, Javascript, Financial Data
Who are we?
Moneyhub empowers financial services firms with complete, detailed, and real-time insight into their customers’ financial needs and status, enabling them to take informed actions. Our highly categorized, data-enriched analytics allow clients to craft personalized customer journeys, leading to enhanced engagement, optimized acquisition and servicing costs, and increased conversion rates.
As an enterprise B2B2C company, our clients roll out our technology to improve their customers journey and enhance their financial outcomes. We do this through an API-first approach that streamlines access to our market-leading Categorisation, Decisioning, and Analytics engines, together with Payments Initiation. In doing so we deliver actionable insights with reduced transaction costs, accelerated settlements, and a safer, more convenient customer experience.
We’re a regulated entity offering AISP, PISP, and CISP services, trusted by leading banks, insurers, asset and wealth managers, pension companies, financial advisors, and fintechs to enhance financial outcomes for their clients.
💰 What do we offer?
We have offices in London and Bristol together with access to co-working space. We offer the opportunity to work remotely (role, business and client dependent) with support for your home office set-up if required. We have regular all company away days and other company, client and team meetings, your attendance at which will be mandatory.
Whilst this will be a remote first role we ask that applicants are based within commutable distance to either London or Bristol for regular in person meetings with the team.
Benefits include:
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
Requirements
👀 Sounds interesting! What will you be doing?
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
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 working within a Start Up / Scale Up technology company
- 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)
Beneficial if you :
- 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
At Moneyhub, we value engineers who can both understand data science concepts and implement them as high-quality, production-ready code. The ideal candidate bridges analytical thinking with practical engineering, delivering solutions that work reliably at scale rather than just proof-of-concepts.
