Marketing Machine Learning Engineer

Cleo
London
3 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

▷ 3 Days Left: Machine Learning Engineer...

Head of Data Science

SC Cleared - Data Engineer - Python, SQL

Data Engineer

Data Engineer (SC Cleared)

At Cleo, were not just building another fintech app. Were embarking on a mission to fundamentally change humanitys relationship with money. Imagine a world where everyone, regardless of background or income, has access to a hyper-intelligent financial advisor in their pocket. Thats the future were creating.

Cleo is a rare success story: a profitable, fast-growing unicorn with over $200 million in ARR and growing over 2x year-over-year. This isnt just a job; its a chance to join a team of brilliant, driven individuals who are passionate about making a real difference. We have an exceptionally high bar for talent, seeking individuals who are not only at the top of their field but also embody our culture of collaboration and positive impact.

If you’re driven by complex challenges that push your expertise, the chance to shape something truly transformative, and the potential to share in Cleo’s success as we scale, while growing alongside a company that’s scaling fast, this might be your perfect fit.

Machine Learning Engineers at Cleo work on building novel solutions to real-world problems. This really does vary but could be: creating chatbots to coach our users around their financial health, creating classifiers to better understand transaction data or even optimising transactions within our payments platform.

Ultimately, we’re looking for a Machine Learning Engineer specialising in Marketing Science to become a cornerstone of our high-performing team. As the first Machine Learning Engineer in this squad, you’ll harness data to unlock insights into channel performance, support to optimise marketing strategies, and drive our growth. Working closely with our Director of Performance Marketing, Marketing Analytics Manager, and cross-functional teams, your work will directly impact how we attract, engage, and retain Cleo’s users.

What You’ll Be Doing

  • Marketing Measurement:Building out some of and improving on Cleo’s marketing measurement toolkit, including Marketing Mix Models (MMM), attribution modelling, and incrementality testing to provide the team with clear insights into the drivers of overall and channel performance.
  • Lifetime Value Modelling:Develop and optimise predictive models that forecast user lifetime value, ensuring data-driven channel optimisation and decisions that maximise Return On Ad Spend.
  • Budget Allocation Tools:Create scalable, automated decision-support tooling that optimises the distribution of our marketing budget across channels. These tools will integrate data from multiple sources including MMM, incrementality tests, and our single source of truth (SSOT) data to maximise ROAS.
  • Marketing Lift Tests:Work with our performance marketing team and marketing platforms (Meta, Tiktok, Apple etc) to design and implement lift studies that enhance our understanding of channel performance & incrementality.
  • Brand Marketing Campaign Analysis:Develop causal inference models to provide deeper insights into the performance and uplift of our brand marketing campaigns on awareness and acquisition.
  • Operational Excellence:Continuously review and refine data processes, collection and tooling, collaborating with engineering to maximise efficiency.

What you’ll need

  • 3+ years in Data Science, with a focus on Marketing Science or a related field.
  • Strong background in statistical analysis, including Marketing Mix Modelling and Predictive LTV modelling.
  • Excellent knowledge of both Data Science (Python, SQL) and production tools (Airflow).
  • Experience of shipping tested models which make predictions in batch or real time.
  • Proven ability to understand stakeholder problems and build models that get used for decision-making, including surfacing the results in tooling or dashboards.

Nice to have

  • A proactive approach to learning new technologies and stepping outside your comfort zone, whether building data pipelines, or integrating data sources.
  • Experience with B2C subscription business models.
  • A keen interest in leveraging advanced analytics to drive financial technology innovations.

What do you get for all your hard work?

  • A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles.You can view our public progression framework and salary bandings here:https://cleo-ai.progressionapp.com/
  • Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures.
  • A clear progression plan.We want you to keep growing. That means trying new things, leading others, challenging the status quo and owning your impact. Always with our complete support.
  • Flexibility.We can’t fight for the world’s financial health if we’re not healthy ourselves. We work with everyone to make sure they have the balance they need to do their best work.
  • Work where you work best.We’re a globally distributed team. If you live in London we have a hybrid approach, we’d love you to spend one day a week or more in our beautiful office. If you’re outside of London, we’ll encourage you to spend a couple of days with us a few times per year. And we’ll cover your travel costs, naturally.
  • Other benefits:
  • Company-wide performance reviews every 6 months.
  • Generous pay increases for high-performing team members.
  • Equity top-ups for team members getting promoted.
  • 25 days annual leave a year + public holidays (+ an additional day for every year you spend at Cleo, up to 30 days).
  • 6% employer-matched pension in the UK.
  • Private Medical Insurance via Vitality, dental cover, and life assurance.
  • Enhanced parental leave.
  • 1 month paid sabbatical after 4 years at Cleo.
  • Regular socials and activities, online and in-person.
  • Well pay for your OpenAI subscription.
  • Online mental health support via Spill.
  • Workplace Nursery Scheme.
  • And many more!
  • We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds.If there’s anything we can do to accommodate your specific situation, please let us know.

Apply for this job

* indicates a required field

J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.