[All remote jobs](https://jobicy.com/jobs.md)[![Monzo logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/5b4c0ec3-221.jpg)](https://jobicy.com/company/monzo.md)[Monzo](https://jobicy.com/company/monzo.md) # Lead Machine Learning Scientist, Search Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/monzo.md)ShareRemote from[UK](https://jobicy.com/job-region/uk.md)SalaryGBP 115k–150k / yrDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentPart TimeExperienceSeniorPublished23 Oct 2026Apply before22 Nov 2026Listing views28Application actions0Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Monzo is seeking a lead-level machine learning scientist to build and deploy search, ranking, personalisation, and decisioning models for consumer banking products. The role is a technical-lead individual-contributor position with end-to-end ownership from ambiguous business problems through measurable production impact. Core work includes embeddings, contextual bandits, personalised ranking, explainable AI, and scalable production ML within a cloud-native data platform. The position requires strong Python, scikit-learn, SQL, product judgment, and the ability to communicate complex ML concepts to non-specialist stakeholders. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a senior technical leadership role requiring advanced production ML expertise, experimentation rigor, and responsibility for models used by more than 15 million customers. The scientist must independently resolve ambiguity while balancing customer outcomes, responsible AI, and measurable commercial impact. ## Salary analysis Estimated compensation compared with the broader UK market for similar roles. Estimated job median (per year)Market rate£132,500UK market range (per year)£120k–£165k0£181.50k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a £115,000–£150,000 compensation range. The posting does not explicitly state the cadence, so yearly pay is inferred from the senior UK role context and the magnitude of the stated range. The estimated UK market range for a lead machine learning scientist is £120,000–£165,000 per year; incentive awards and benefits are additional and are not included in the base-pay estimate. ## Core skills Skills and capabilities most closely associated with this opportunity. [Machine Learning](https://jobicy.com/jobs?search_keywords=Machine%20Learning.md)[Search Ranking](https://jobicy.com/jobs?search_keywords=Search%20Ranking.md)[Personalisation](https://jobicy.com/jobs?search_keywords=Personalisation.md)[Recommendation Systems](https://jobicy.com/jobs?search_keywords=Recommendation%20Systems.md)[Contextual Bandits](https://jobicy.com/jobs?search_keywords=Contextual%20Bandits.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[scikit-learn](https://jobicy.com/jobs?search_keywords=scikit-learn.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Model Deployment](https://jobicy.com/jobs?search_keywords=Model%20Deployment.md)[MLOps](https://jobicy.com/jobs?search_keywords=MLOps.md)[Embeddings](https://jobicy.com/jobs?search_keywords=Embeddings.md)[Explainable AI](https://jobicy.com/jobs?search_keywords=Explainable%20AI.md)[Experiment Design](https://jobicy.com/jobs?search_keywords=Experiment%20Design.md)[Microservices](https://jobicy.com/jobs?search_keywords=Microservices.md)[Product Analytics](https://jobicy.com/jobs?search_keywords=Product%20Analytics.md) Sample interview questionsHow would you approach improving search relevance for a banking application with diverse customer intents?I would begin by defining key search intents and success metrics such as successful task completion, reformulation rate, click-through rate, and downstream product outcomes. I would combine behavioural signals, content and product metadata, and user context to build a staged retrieval-and-ranking system, then validate improvements through offline evaluation and controlled online experiments. Describe how you would evaluate a contextual bandit model before and after production deployment. Before deployment, I would assess offline policy value using logged-bandit evaluation methods where appropriate, test calibration and safety constraints, and compare against a stable baseline. In production, I would use a guarded rollout with clear reward definitions, monitoring for segment-level performance and unintended outcomes, and rollback criteria for customer or business risk. How do you make an ML solution explainable and responsible in a consumer financial setting? I would incorporate explainability requirements during problem formulation, use understandable features and model behaviour where possible, document limitations, and evaluate outcomes for customer segments. I would also implement governance, privacy-aware data handling, fairness testing, human review where warranted, and monitoring for drift or harmful recommendations. Tell us about a time you turned an ambiguous business problem into a measurable ML product. I would explain how I aligned stakeholders on the customer problem and decision to improve, translated that into measurable metrics, established a baseline, and iterated through experiments. A strong example would also cover production delivery, trade-offs made, and evidence that the solution improved the intended customer or business outcome. How would you work with backend engineers and product managers to productionise a ranking model? I would agree on the decision flow, latency budget, model interface, data contracts, ownership, and success metrics early. I would partner with engineers on reliable feature generation, serving, monitoring, and rollback mechanisms, while ensuring product stakeholders understand expected behaviour, experimentation plans, and metric trade-offs. Opportunity details ## About this role. 🚀 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](https://monzo.com/current-account/personal) and [business](https://monzo.com/business-banking) bank accounts, we offer [joint accounts](https://monzo.com/current-account/joint-account), [accounts for 16-17 year olds](https://monzo.com/current-account/16-17), a [free kids account](https://monzo.com/current-account/under-16s) and [credit cards](https://monzo.com/flex) in the UK, with more exciting things to come beyond. Our UK customers can also [save](https://monzo.com/savings), [invest](https://monzo.com/investments)and [combine their pensions](https://monzo.com/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 | 💰 £115,000 – £150,000 + Incentive Awards tied to your performance + [Benefits](https://monzo.com/careers/) ✨ ### About our Machine Learning Search Team We are currently embarking on one of our two top strategic priorities to make Money work for Everyone: building the Monzo Co-pilot. We are becoming an intelligent, proactive ally that handles the complexity of users financial life. We aren’t just selling financial products; we are building a truly smart agent that understands users, anticipates their needs, and helps people reach their financial goals. Our ML Search team brings together Backend, Product, Machine Learning Scientists and Data Scientists. As a Lead Machine Learning Scientist, you’ll build and ship models that help customers search for and find answers about their financial lives. You’ll make it effortless for them to find the right products at the exact moment they need them. Whether it’s surfacing the right savings product at the perfect moment, helping customers manage their spending, or simplifying financial planning, our work makes banking smarter, more intuitive, and truly customer-first. ### What you’ll be working on: As a Lead Machine Learning Scientist, you’ll be a technical leader and individual contributor. We have a modern, cloud-native data platform with billions of rows of data built for fast iterations. You’ll leverage your deep expertise to develop and deploy advanced ML models to our more than 15 million customers. Your work may involve user and product embeddings to better understand customer behaviours, contextual bandits for optimising real-time decisions, or personalised ranking algorithms that improve search and discovery. You’ll also build scalable, explainable, and responsible AI solutions that enhance trust, transparency, and the overall customer experience. The technical approaches you take to help solve customer problems will be very much in your hands and we’ll strongly encourage and support experimentation and innovation. We’ll be expecting you to justify and demonstrate effectiveness along the way, making sure the approach meets our business and customer needs. ### You should apply if: What we’re doing here at Monzo excites you! * You have a multiple year track record of excellence leading the development and deployment of advanced Machine Learning models to tackle real business problems preferably in a fast moving tech company * You have experience developing and shipping state of the art ML models to production and delivering business impact * You’re impact driven and excited to own the end to end journey that starts with a business problem and ends with your solution having a measurable impact in production * You have a self-starter mindset; you proactively identify issues and opportunities and tackle them without being told to do so * You speak Python fluently and have extensive, hands-on experience with scikit-learn. You are comfortable using SQL, and keen to learn [Go lang](https://go.dev/) which is used in many of our backend microservices * You’re comfortable working in a team that deals with ambiguity and have experience helping your team and stakeholders resolve that ambiguity * You want to be involved in building a product that you (and the people you know) use every day * You have a product mindset: you care about customer outcomes and you want to make data-informed decisions * You’re excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain * You’re adaptable, curious and enjoy learning new technologies and ideas ### Nice to haves: * Experience working on personalisation, ranking & recommendation problems for consumer applications * Commercial experience writing critical production code and working with microservices ### The interview process: Our interview process involves 3 main stages. We promise not to ask you any brain teasers or trick questions! 30 minute recruiter call 45 minute call with hiring manager Full Loop: ML Modelling Interview, Product & ML interview, Behavioural Interview, Leadership interview Our average process takes around 3-4 weeks but we will always work around your availability. ### What’s in it for you: ✈️ 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 training courses and conferences ➕And much more, see our full list of benefits [here](https://monzo.com/careers/) If you prefer to work part-time, we’ll make this happen whenever we can – whether this is to help you meet other commitments or strike a great work-life balance #LI-REMOTE #LI-SR1 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](https://monzo.com/blog/diversity-and-inclusion), 2026 [Diversity and Inclusion Report](https://monzo.com/blog/our-2026-diversity-and-inclusion-report) and 2025 [Gender Pay Gap Report.](https://monzo.com/blog/gender-pay-gap-report-2025) 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 😊 Show more [Apply now >](https://jobicy.com/jobs/156506-lead-machine-learning-scientist-search.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content. Next step ## Apply now. Follow the employer’s application method and review Jobicy’s safety guidance before sharing personal information. Keep exploring ## Related remote jobs. * ![Nebius logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2026/06/d90c0566-221.webp) Nebius Oct 23 New ### [Senior Data Engineer](https://jobicy.com/jobs/156537-senior-data-engineer-5.md) About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. 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