Senior Analytics Engineer

Monzo

🚀 We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts, accounts for 16-17 year olds, a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save, invest and combine their pensions with us.  With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We’re not about selling products - we want to solve problems and change lives through Monzo ❤️ ----------------------------------------------------------------------------------------------------------------------------------   Staff Analytics Engineer - Borrowing 📍London/Cardiff/UK Remote | 💰 £121,600-164,600 + stock and benefits | Hear from the team ✨ ⭐ Our Borrowing Analytics Engineering Team   Our mission in Borrowing is to help people achieve their financial goals through better borrowing. Our customers borrow money to achieve something in their lives — whether that’s making a big life event affordable, buying something they need now without affecting their monthly budget, or getting by until payday. We’re shaping this mission by building products our customers love, while safely scaling some of Monzo’s biggest revenue lines. Borrowing is one of Monzo’s most complex and fastest-growing domains. We operate 12+ products across multiple geographies, underpinned by 1,700+ data models and an analytics engineering team that’s scaling to match. We’re in the middle of a major data architecture transformation, expanding into new markets, and building the next generation of data infrastructure to support it all. We’re looking for a Staff Analytics Engineer to help shape how Borrowing builds and uses data at scale. Reporting to the Borrowing Data Director, you’ll work across product, credit, engineering, Data Platform, and analytics engineering teams to turn complex technical problems into clearer systems, stronger data products, and better business decisions.     🔑 You’ll play a key role by… * Architecting Borrowing’s data layer at scale. Partnering across Analytics Engineering, Product, Engineering, Credit, and Data Platform to shape how 1,700+ models across 12+ products are structured, connected, and evolved. You’ll set shared patterns that help teams build trusted, consistent, and scalable data products across Borrowing. * Designing and governing data products. Moving us beyond ad-hoc tables toward well-defined, contractual data assets with clear ownership, SLAs, documentation, and interfaces. You’ll work with teams across Borrowing and Data Platform to define what makes a Borrowing dataset “production-grade” and consumable by analytics, ML, decisioning, and regulatory teams. * Building feature stores and reusable analytical assets. Identifying cross-product signals (credit behaviour, repayment patterns, affordability, risk indicators) that should be modelled once, tested rigorously, and consumed by many. You’ll design the layer that turns raw product data into curated, versioned features that power models, dashboards, and decisions. * Scaling our analytics engineering infrastructure. Shaping the tooling, patterns, and developer experience that make an 80+ person credit and data organisation more productive. This means influencing our data architecture and ways of working across data and credit disciplines, while partnering with the central Data Platform team to ensure Borrowing’s needs are reflected in ingestion, streaming, and schema contract design. * Driving cross-product data consistency. As we expand across geographies and product lines, ensuring our data models are coherent and comparable. You’ll work with AE leads and domain experts to define shared conventions and abstractions that allow us to reason about Borrowing as a whole, not just product-by-product. * Being a senior technical partner for Borrowing’s data estate. Partnering with backend engineers on source data payload design, with product managers on measurement strategy, with credit teams on decisioning data, and with senior leadership on what’s possible and what’s next. * Leading through influence and leverage. You won’t manage people directly, but you’ll shape how an entire domain builds data. You’ll multiply the impact of AEs across Borrowing by setting the right patterns, unblocking architectural decisions, and raising the bar on what good looks like.   🤩 We’d love to hear from you if… * You think in systems, not just queries. You’ve designed data architectures that span multiple products or domains, and you know how to keep them coherent as they scale. You can take ambiguous problems and turn them into a clear technical direction, delivery sequence, and set of trade-offs. * You’ve built data products, not just data models. You understand the difference between a table that exists and a data asset that’s governed, documented, versioned, discoverable, and trusted. You’ve defined SLAs, contracts, interfaces, or ownership models for data consumers, and you’re excited to do this at scale. * You have deep fluency with analytics engineering systems and infrastructure. dbt at scale, BigQuery or equivalent, CI/CD for data, testing frameworks, and orchestration. You don’t just use these tools, you shape how teams use them. You’ve hit the scaling limits and know what to do about them. * You can design reusable feature layers. You’ve designed, contributed to, or have a clear vision for reusable feature layers that serve multiple consumers, including ML pipelines, dashboards, decisioning engines, and regulatory reporting. You understand the trade-offs between freshness, cost, granularity, correctness, and ease of use. * You’re comfortable at the platform boundary. You can have a productive conversation with a Data Platform engineer about ingestion patterns, streaming vs. batch trade-offs, schema evolution, and infrastructure costs. You don’t need to build the platform, but you need to shape what it delivers. * You connect technical choices to business outcomes. You care about whether data models, feature layers, and platform patterns actually improve decisions. You understand how product, credit, engineering, and operational teams use data, and you use that context to align people around better technical choices. * You lead through others. You create leverage not by writing more SQL, but by setting patterns, reviewing designs, unblocking teams, and raising the standard. You’re energised by making 30+ people more effective, not by being the single expert. * You communicate across altitudes. You can whiteboard a data architecture with a back-end engineer in the morning and present a strategic data roadmap to a director in the afternoon. You adapt your message to your audience without losing precision. * You care about credit products. You’re excited, or curious, about the complexity of lending, including risk, affordability, regulatory constraints, and multi-product dynamics. You see it as a fascinating data domain, not just a business vertical. Interview process Our typical process is structured as: * Recruiter call * Initial call   * 3 x 1 hours sessions (final interview) Our average process takes around 3-4 weeks but we will always work around your availability.  What’s in it for you: 💰 £121,600-164,600 base  ✈️ We can help you relocate to the UK  ✅ We can sponsor visas  📍This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London). ⏰ We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team. 📚 Learning budget of £1,000 a year for books, training courses and conferences ➕ And much more, see our full list of benefits here #LI-AS #LI-Remote ---------------------------------------------------------------------------------------------------------------------------------- Equal opportunities for everyone Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog, 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report. We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status. If you have a preferred name, please use it to apply. We don't need full or birth names at application stage 😊

Monzo

🚀 We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts, accounts for 16-17 year olds, a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save, invest and combine their pensions with us.  With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We’re not about selling products - we want to solve problems and change lives through Monzo ❤️ ----------------------------------------------------------------------------------------------------------------------------------   📍London/Cardiff/UK Remote | 💰 £93,000-120,000 + Incentive Awards tied to your performance + benefits | Hear from the team ✨  About us: At Monzo we want to make money work for everyone. We care deeply about our 15+ million customers. Through magically simple products and actionable insights, we put our customers in control of their finance. Our products are different by design, and reliable at our core. Our range of borrowing products are critical to Monzo’s mission. Not only do they serve important needs of our customers, they are also a key revenue driver to support Monzo keep delivering great products and experience. We have seen stellar growth and deep engagement with millions of borrowers, supported by effective and efficient credit risk management. Our product portfolios are still expanding fast, from personal to business credit, and markets beyond UK. We are looking for bright, passionate and creative individuals to further accelerate our growth. About the role The mission of Borrowing ML Scientists is to improve the customer and business outcomes through better automated decisioning, using Machine Learning and Statistical modelling. We have a primary focus in credit risk modelling, with our expertise also applied to predict and optimise utilisation, pricing, collection and marketing. You will be working alongside a team of very experienced and highly efficient ML Scientists, with well established toolings for the fully lifecycle of ML models. Each of you owns multiple ML applications end-to-end, from experiment design and data curation, to deployment and monitoring. You will be empowered to innovate in the data, methodologies and toolings, so we can build better models easier and faster. You will have exposure to all Borrowing products and applications, with autonomy to decide what are the most impactful topics to work on, and how to deliver them. You will work closely with our Credit Strategy Managers, Model Validation Analysts, Backend Engineers, and Product Managers, to fit your model development into the product roadmap. You are also empowered to think big about the business, market and customers, to influence our product and credit strategy beyond just the world of models. Our technology stack We rely heavily on the following tools and technologies (although we do not expect applicants to have prior experience of all them): * Google Cloud Platform for all of our analytics usages * BigQuery SQL and dbt for our data modelling and warehousing * PyData stack for model development and offline deployment * Google Vertex AI platform for cloud computing * AWS for backend infrastructure * Python for ML model microservices * Go lang for most other microservices * AI toolings for productivity (an evolving list) * Google suites including access to Gemini * ChatGPT enterprise * Claude code 🤩 You should apply if: * You are result oriented and motivated by the impact on our customers and business * You enjoy a high degree of autonomy and thrive in a fast-paced environment * You are keen to grow your knowledge in both business and technology 📌 You must have: * Excellent SQL and Python skills with good understanding of best practices in software engineering and data engineering * In-depth knowledge of statistical and machine learning models: gradient boosted trees, logistic regression, neural networks, survival analysis, etc * Solid knowledge of statistics: hypothesis testing, confidence intervals, bootstrap * Experience of end-to-end model development and maintenance of ML models used for business critical automated decisioning, in a consumer facing industry * Great attention to details while keeping an eye on the big picture * Excellent communication skills to articulate complex problems * Capability to build mutual respect and trust with people of different background Nice to have: * Experience in UK/EU retail lending businesses for personal/business customers * Experience of ML model governance in a regulated industry * Experience in leverage modern day AI tools for productivity The Interview Process: Our interview process involves: * 30’ Recruiter Call * 45’ Initial Call * 60’ ML technical skill interview * 60’ Behavioural interview All interviews will be conducted through Google Meet. What’s in it for you: 💰 £93,000 to £120,000 ➕ plus stock options & benefits ✈️ We can help you relocate to the UK ✅ We can sponsor visas 📍This role can be either based in our London office with hybrid working pattern, or fully remote within UK with occasional travels to London. 🏡We will set you up to work from home; all employees are given Macbooks and for fully remote workers we will provide extra support for your work-from-home setup. ⏰ We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team. 📚 Learning budget of £1,000 a year for books, training courses and conferences ➕ And much more, see our full list of benefits here #LI-DC2  #LI-Remote   ---------------------------------------------------------------------------------------------------------------------------------- Equal opportunities for everyone Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog, 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report. We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status. If you have a preferred name, please use it to apply. We don't need full or birth names at application stage 😊

Monzo

🚀 We’re on a mission to make money work for everyone. We’re waving goodbye to the complicated and confusing ways of traditional banking. After starting as a prepaid card, our product offering has grown a lot in the last 10 years in the UK. As well as personal and business bank accounts, we offer joint accounts, accounts for 16-17 year olds, a free kids account and credit cards in the UK, with more exciting things to come beyond. Our UK customers can also save, invest and combine their pensions with us.  With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments for our customers! We’re not about selling products - we want to solve problems and change lives through Monzo ❤️ ----------------------------------------------------------------------------------------------------------------------------------   London/Cardiff/UK Remote | 💰 £150,000–£180,000 + Incentive Awards tied to your performance + Benefits✨ OUR WORKFORCE SYSTEMS TEAM ⭐ Customer Operations at Monzo is at the heart of delivering fast, safe and high-quality support to millions of customers. As Monzo grows, the way we run operations is evolving. We’re supporting more customers, more products, more markets, more regulatory expectations, and a growing mix of human and AI-powered service. This creates one of the most interesting operational systems challenges at Monzo: how do we forecast demand, plan supply, schedule work, route tasks, understand live performance, and make capacity decisions across an increasingly complex global operation? Workforce systems are central to this. They help determine how Monzo matches customer demand with human and AI capacity, how we protect service levels, how we make cost and capacity trade-offs, and how we keep support fast, safe and reliable as we scale. The next phase is about building the workforce systems that allow Monzo to keep scaling Customer Operations as we expand our products, global footprint and AI capabilities - supporting our mission to make money work for everyone. This role will lead that next phase. You’ll sit at the intersection of Data, Product, Engineering, Operations and Finance. You’ll shape the technology, data products and operating systems that help Monzo understand demand, plan capacity, schedule work, measure execution, assign tasks, and respond to live operational change. You’ll work on capabilities that make workforce decisions more accurate, more automated, more explainable and more resilient as the business grows. You’ll also build and develop the team and capability needed for this next stage - raising the bar for forecasting, measurement, operational data products and system-led workforce decisioning. You don’t need to come from a traditional Workforce Management or contact centre background. We’re looking for a senior data-product systems leader who can reason from first principles, build scalable operational systems, and lead through ambiguity across multiple disciplines. 🔑 YOU’LL PLAY A KEY ROLE BY… * Leading the strategy for Monzo’s Workforce Systems, across forecasting, capacity planning, scheduling, work status, task assignment and service performance. * Building and developing a high-performing team across forecasting, measurement, analytics and operational data products, while helping shape the wider workforce systems roadmap with Product and Engineering. * Building production-grade data products that support live operational decisions - including forecasting, schedule fit, work-status signals, capacity impact, throughput and service-performance measures. * Improving how we forecast and plan demand, including forecast accuracy, bias, uncertainty, feedback loops, and the impact of new products, new markets, AI agents and changing customer behaviour. * Connecting forecasts, schedules and live execution, so teams can understand how operational reality is changing and take action at the right time. * Developing stronger system controls for capacity decisions, including forecast releases, demand changes, operational process changes, tooling launches and staffing decisions. * Evolving how Forecast Change Requests and capacity-impacting changes work, moving toward system-supported decisioning, impact assessment and guardrails. * Partnering deeply with Product and Engineering to define and build the workflows, metrics, controls and technical capabilities that help teams make better workforce decisions. * Helping evolve task assignment and routing, so work is allocated based on schedule, skill, capacity, prioritisation logic and live service needs. * Raising the analytical and statistical bar across workforce planning and service performance, helping teams reason clearly about forecast error, AHT, workload, volatility, throughput, schedule adherence and customer outcomes. * Transforming the operating model for the next stage of scale, helping teams move toward exception-based operation, feedback loops and system-led control. * Working with senior leaders across Ops, Data, Product, Engineering and Finance to make trade-offs between service quality, cost, capacity, risk and speed of execution. 🤩 WE’D LOVE TO HEAR FROM YOU IF… * You’ve led data products, forecasting systems, marketplace systems, logistics systems, operational platforms or live decision systems where data and models directly influenced how a business operated. * You have strong first-principles systems thinking and can break complex operational problems into clear components, feedback loops, controls and product opportunities. * You have strong statistical judgement - you understand forecasting, uncertainty, bias, volatility, measurement quality, and when a metric is ready to support an operational decision. * You’re product-minded: you think about users, workflows, incentives, adoption, decision points, and how tooling can make good decisions easier. * You’re credible with Engineering and can partner on architecture, reliability, system design, productisation, sequencing and trade-offs. * You’ve built, led or scaled teams working across data, product, engineering or operational systems. * You’re comfortable working in live operational environments, where decisions affect customers, cost, risk, regulation and service performance. * You can lead through ambiguity and influence senior stakeholders across Product, Engineering, Data, Ops and Finance. * You’re a builder-leader: you’ve created teams, systems, processes or capabilities that scale. * You’re excited by the challenge of building workforce systems for a future where human and AI capacity operate together. * You’re motivated by Monzo’s mission to make money work for everyone, and by the role Operations plays in delivering fast, safe and high-quality customer support as we grow. 👀 YOUR BACKGROUND COULD LOOK LIKE… You may have worked in data science, data products, operational systems, forecasting, marketplace operations, logistics, planning systems, routing, service platforms, AI-enabled operations, or another complex supply/demand environment. Experience in Workforce Management, customer operations, outsourcing, or contact centres would be useful, but it’s not required. We care more about your ability to understand complex systems, build data products that power operational decisions, and lead across Data, Product, Engineering and Operations. You also don’t need to be the deepest hands-on forecaster or ML engineer yourself, but you should know what good looks like, set a high bar, and build the team and systems around you. 🌍 THE OPPORTUNITY This is a senior technology and data leadership role focused on building the next generation of workforce systems at Monzo. The role sits at the intersection of Data Science, Product, Engineering and Operations. It needs someone who can bring statistical judgement, product thinking, technical credibility and people leadership together to shape systems used in live operational decision-making. You’ll help Monzo continue to scale Customer Operations as our product set, customer base, AI capabilities and global footprint grow. That means building systems that help us serve customers quickly and safely, use human and AI capacity well, and make high-quality operational decisions in increasingly complex environments. 🙌 WHAT’S IN IT FOR YOU 💰 £120,000–£175,000 + Benefits ✈️ We’ll help you relocate to the UK, if applicable ✅ We can sponsor your visa 📍 This role can be based in our London office, but we’re open to distributed working within the UK, with occasional meetings in London ⏰ We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team 📚 £1,000 learning budget each year to use on books, training courses and conferences 🏡 We’ll set you up to work from home; all employees are given MacBooks and remote workers get extra support for their home setup ➕ Plus lots more - read our full list of benefits 🧠 OUR INTERVIEW PROCESS We focus on real-world problem solving - not brainteasers. Our process usually includes: * 30 minute recruiter call * 45 minute hiring manager call * Interviews with senior leaders across Data, Product, Engineering and Operations We’ll explore how you think about: * building data products that operate inside live systems * forecasting, uncertainty and operational measurement * designing systems, controls and feedback loops * cross-functional leadership * service performance and operational trade-offs * building teams and capabilities for scale Our average process takes around 3-4 weeks, and we’ll always work around your availability ---------------------------------------------------------------------------------------------------------------------------------- Equal opportunities for everyone Diversity and inclusion are a priority for us and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. You can read more in our blog, 2026 Diversity and Inclusion Report and 2025 Gender Pay Gap Report. We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status. If you have a preferred name, please use it to apply. We don't need full or birth names at application stage 😊