
Multiverse · London
Multiverse is the upskilling platform for AI and Tech adoption. We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming t...
Multiverse is the upskilling platform for AI and Tech adoption.
We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce.
Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills.
Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable
performance.
In April 2026, we announced $70 million in strategic funding, led by Schroders Capital, with participation from StepStone Group,
Lightspeed Venture Partners and General Catalyst. At an increased valuation of $2.1bn, the round makes us Europe’s first EdTech
double unicorn.
But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling.
We’re building a world where tech skills unlock people’s potential and output.
Join Multiverse and power our mission to equip the workforce to win in the AI era.
At Multiverse, the models we build don't just sit in notebooks - they drive the decisions that shape our business every day. From
predicting learner outcomes to forecasting operational demand and optimising how we allocate resources, this work sits at the very
core of how we run the company.
As a Senior Data Scientist, you'll own these models end to end. You'll develop a deep understanding of how Multiverse operates
across our customer, learner and operational domains - and translate that understanding into rigorous, production-grade ML models
that genuinely move the needle. To be successful, you'll be comfortable getting hands-on with pipelines and infrastructure - and
unafraid of the statistical rigour that serious modelling demands.
You'll work closely with stakeholders across every part of the business - helping them ask better questions, understand the
answers, and act on them with confidence. Our leaders will make multi-million dollar decisions based on your recommendations, and
our AI-powered product will decide how to support learners based on your models.
You'll sit within our Data & Insight team, working day-to-day alongside Data Engineers, Data Product Developers and Insight
Analysts.
Business Understanding & Problem Definition
thought partner
accordingly
Modelling & Statistical Analysis
business
being made
account for them
Data Engineering & Infrastructure
deploy your models
CI/CD and vulnerability management
Required
business decisions
principles
Desirable
or economics)
Benefits
(M-Powered Weekend) and 8 bank holidays per year
resources through Wellhub and access to Spill - all in one mental health support
Instructors who collaborate in the office once a month
stocked!
Our Commitment to Diversity, Equity and Inclusion
We’re an equal opportunities employer. And proud of it. Every applicant and employee is afforded the same opportunities regardless
of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability,
gender, gender identity or expression, or veteran status. This will never change. Read our Equality, Diversity & Inclusion policy
here.
Our Commitment to Safeguarding
Multiverse is committed to safeguarding and promoting the welfare of our learners. We expect all employees to share this
commitment and adhere to our Safeguarding Policy, our Prevent Policy and all other Multiverse company policies. Successful
applicants will be required to undertake at least a Basic check via the Disclosure Barring Service (DBS).
For roles that will involve a Regulated Activity, successful applicants must also undergo an Enhanced DBS check, including a
Children’s Barred List check and a Prohibition Order check. Roles involving Regulated Activity may interact with vulnerable
groups, therefore are exempt from the Rehabilitation of Offenders Act 1974 meaning applicants are required to declare any
convictions, cautions, reprimands, and final warnings.
Providing false information is an offence and could result in the application being rejected or summary dismissal if the applicant
has been selected, and possible referral to the police and the DBS.
OUR MISSION To become the car-changing destination of choice. By combining technology, media and deep automotive expertise, we've turned how people buy, sell, advertise and lease cars on its head. What started as a simple reviews site is now one of the largest online car-changing destinations in Europe. Last year alone we grew over 50% with nearly £3bn worth of cars bought on site, while £1.8bn of cars were listed for sale through our Sell My Car service. In 2024 we went big and acquired Autovia - creators of AutoExpress and Evo magazines - doubling our audience overnight. Together we now have one of the biggest YouTube channels in the world with almost 10m subscribers and over 1.1 billion annual views, while we sell 1.2 million print copies of our magazines and have an annual web content reach over 350million. And we’re a long way from done! THE ROLE We're looking for a Senior Data Scientist to join our award-winning Data Science team at a pivotal moment. Carwow operates a two-sided marketplace — connecting car buyers and sellers at scale — and data science sits at the heart of how we make that marketplace smarter, faster, and more valuable for everyone in it. In fact, we recently won GenAI initiative of the Year at the British Data Awards. This is a hands-on, high-ownership role working centrally across the business. You'll partner with teams spanning Commercial, Marketing, Product, Finance, Engineering and Operations — developing and deploying ML and AI solutions that drive outcomes across both sides of our marketplace. The problems you'll work on are genuinely varied: pricing models, propensity and demand signals that sharpen marketing spend, personalised recommendations for our web product and CRM, and LLM-powered solutions for operational challenges like document verification. You'll translate ambiguous business problems into structured, production-ready solutions — and you'll be expected to deliver them end-to-end, from first principles through to being deployment-ready and beyond. WHAT YOU'LL BE DOING * End-to-End ML & AI Delivery: Lead data science initiatives from problem framing through to deployment, monitoring, and iteration — delivering the full production lifecycle. With no dedicated ML engineering function, you'll be responsible for ensuring your solutions are robust, scalable, and performing in the real world long after they ship. * GenAI & LLM Application: Design and build LLM-powered solutions where they create genuine business value — document processing, intelligent search, content understanding, and beyond. Apply them alongside classical ML with clear judgement about where each approach earns its place. * Commercial Impact: Connect your work directly to business outcomes. Whether you're building a model to improve marketing efficiency, a pricing signal to sharpen commercial decisions, or a recommendation engine to increase conversion — you understand the business lever you're pulling and design your solutions accordingly. * Prototyping & Experimentation: Move fast to test ideas before committing to full-scale development. Define rigorous success metrics upfront, validate honestly, and know when to double down and when to walk away. * Cross-Functional Partnership: Work closely with Commercial, Marketing, Product, Finance, Engineering and Operations stakeholders to understand problems deeply before reaching for a solution. Translate findings into clear, actionable narratives for both technical and non-technical audiences. * Standards & Craft: Contribute to shared best practices, documentation, and ways of working that raise the bar for the data science function — and help more junior team members grow alongside you. Drive continued adoption of AI capabilities to drive efficiencies, automation and constantly leverage new capabilities. WHAT YOU'LL NEED Please note: We know that no candidate will be the perfect match for all we've listed in this posting, so we’d encourage you to apply if you feel you're close to the brief but not an exact match. Ideally you’ll have * Commercial Mindset: You think about business impact first. You understand how your models connect to revenue, efficiency, or customer outcomes — and you use that to prioritise, scope, and communicate your work. * Stakeholder Partnership: Proven ability to work with commercial, marketing, and product stakeholders — translating business problems into well-scoped solutions and communicating technical solutions, challenges and outcomes clearly at all levels. * Sound Judgement: You navigate the tooling landscape with clear eyes — knowing when classical ML is right, when GenAI unlocks something new, and when a simpler solution is the more honest answer. Strong instincts for scalability, reliability, and explainability. * [Bonus] Marketplace or Two-Sided Platform Experience: Understanding of supply/demand dynamics and how data science creates leverage in a marketplace context. TEHCNICAL SKILLSET * Proven ML Experience: A strong track record of building, deploying, and maintaining ML models in Python in a production environment — not just notebooks. You've owned models after they ship and know how to keep them healthy. * Full-Lifecycle Delivery (MLOps): Comfortable delivering the end-to-end production lifecycle — model training, versioning, monitoring, and champion/challenger experimentation — without relying on a dedicated ML engineering team to carry that responsibility. * GenAI & LLM Expertise: Hands-on experience building LLM-powered solutions that deliver measurable business value. You understand how to apply, evaluate, and extend these tools — and you're honest about where they fall short. * Technical Depth: Solid experience in a cloud ML environment with software engineering principles — version control, code reviews, unit testing, and familiarity with containerisation. * Quantitative Rigour: Strong foundation in statistical evaluation and experiment design. You can define and defend success metrics, and you know when a model is degrading and what to do about it. * [Bonus] Experience with VertexAI TOOLS & TECHNOLOGIES * Languages: Python, SQL * Data & Transformation: dbt, Snowflake, BigQuery * Visualisation & BI: Looker * Engineering & MLOps: Docker, GitHub * Workflow & Orchestration: Vertex AI Pipelines (GCP), Kubeflow * LLMs & GenAI: Gemini API, Claude API INTERVIEW PROCESS * Step 1: People Team Screening Call (30 min) * Step 2: Hiring Manager Call: Experience (45 min) * Step 3: Technical Task: covering both Modelling & Production with Presentation (60 min + Task) * Step 4: Values Interview (45 min) WHAT’S IN IT FOR YOU * Hybrid working * Competitive salary to fund that dream holiday to Bali * Matched pension contributions for a peaceful retirement * Share options - when we thrive, so do you! * Vitality Private Healthcare, for peace of mind, plus eyecare vouchers * Life Assurance for (even more) peace of mind * Monthly coaching sessions with Spill - our mental wellbeing partner * Enhanced holiday package, plus Bank Holidays * 28 days annual leave * 1 day for your wedding * 1 day off when you move house - because moving is hard enough without work! * For your third year anniversary, get 30 days of annual leave per year * For your tenth year anniversary, get 35 days of annual leave per year * Option to buy 3 extra days of holiday per year * Work from abroad for a month * Inclusive parental, partner and shared parental leave, fertility treatment and pregnancy loss policies * Bubble childcare support and discounted nanny fees for little ones * The latest tech (Macbook or Surface) to power your gif-sending talents * Up to £500/€550 home office allowance for that massage chair you’ve been talking about * Generous learning and development budget to help you master your craft * Regular social events: tech lunches, coffee with the exec sessions, lunch 8 learns, book clubs, social events/anything else you pester us for * Refer a friend, get paid. Repeat for infinite money Diversity and inclusion is an integral part of our culture. We know that diverse teams are strong teams, so we welcome those with alternative identities, backgrounds, and experiences to apply for this position. We make recruiting decisions based on experience, skills and potential, so all our applicants are treated fairly and equally.
By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalized than ever before. Learn more at geniussports.com. The Role You will join a team of data scientists developing the next generation of Genius Sports’ market leading sports models. These models act as the sporting brain behind many of Genius’s customer facing products, calculating the probabilities of outcomes across a wide range of sports. How will you work? Join a specially formed, highly skilled team delivering an innovative & intelligent product! Forming part of a multi-disciplinary Agile team of Software Engineers, Data Scientists, QA Engineers and a Product Manager, you will look to work closely to the fundamental principles of continuous delivery and empowered, high-performing teams. We operate in a squad model to allow focus on the business top priorities, allowing exposure across multiple products while still maintaining strong ownership of your team’s domain. If you are looking to tackle hard problems, collaborate with high calibre engineers and deliver smart solutions with an autonomous & performance focused approach that supports success, delivery & quality, then this is for you. As a Senior Data Scientist, you and your team will play a major role in developing and implementing predictive models across all major sporting codes. You will prototype, implement, evaluate and optimize algorithms to calculate the probabilities of sporting outcomes. What skills do you have? * A BSc, MSc or PhD in Data Science, Mathematics, Computer Science, Computational Statistics, Machine Learning or other STEM subject * Expert understanding of probability and statistics fundamentals * Proficiency with Python or other scripting/programming languages (R, Matlab, etc) * Expertise in a broad range of data science / machine learning algorithms (Monte Carlo simulation, neural networks, logistic regression, random forest, etc.) with a proven track record of delivering solutions to complex problems. * Ability to bring clarity to complex domains, rapidly developing a deep understanding and challenging unclear requirements. You lead conversations that drive alignment and uncover edge cases others might miss. * Mentoring of other team members, helping them develop their skills and deliver effectively It is advantageous for you to have knowledge of the following: * Sports rules and strategies * Sports betting * Machine Learning Operations (MLOps) covering the full life cycle from model creation, deployment (Gitlab, AWS, Docker) and retraining * Data engineering * Rust, C++, other programming languages * Real-time systems and/or high-performance computing What we expect from our co-workers * Curiosity and strong desire to learn and improve * Social skills, being able to act as a facilitator, can balance enabling others with individual contributions. * Time management and asynchronous communication skills relevant for a geographically diverse engineering organization * Enthusiasm and ability to work collaboratively within a team * Excellent spoken and written English * Adherence to our core engineering principles of Aligned Autonomy, Psychological Safety and Continuous Improvement We enjoy an ‘office-first’ culture and maximize opportunities to collaborate, connect and learn together. Our hybrid working models differ depending on your role and location. Occasional travel may be required. As well as a competitive salary and range of benefits, we’re committed to supporting employee wellbeing and helping you grow your skills, experience and career. Learn more about how rewarding life at Genius can be at Reward | Genius Sports. One team, being brave, driving change We strive to create an inclusive working environment, where everyone feels a sense of belonging and the ability to make a difference. Learn more about our values and culture at Culture | Genius Sports. Let us know when you apply if you need any assistance during the recruiting process due to a disability.
We’re on a mission to make migration easy. We started building Marshmallow in 2017. Since then, we’ve grown from 3 to 700+ people, gained unicorn status, raised ~£140M over three funding rounds, turned profitable, insured millions of drivers and lent millions in car loans. But we’re only just getting started. Our goal is to become one of the largest financial services providers in the world. Over the next 10 years we’ll grow exponentially, not only by scaling our existing products, but also by building new ones. To achieve our goals we need incredibly ambitious, commercially driven people who never settle for ‘good enough’. Marshmallowers are hungry for autonomy and ownership, and would rather improve than coast. Everyone raises standards and has an impact, with a focus on collective success over self-interest. We’ve created an environment where curious, tenacious people win and grow together. If that sounds motivating, this could be the place for you. LONDON (HYBRID, 3 DAYS IN OFFICE) DATA SCIENCE AT MARSHMALLOW Our Data Science team partners across the business to turn data into better decisions, smarter products, and simpler customer journeys. We work closely with Product, Engineering, and Operations to build and ship models and AI systems that are reliable in production and deliver measurable impact. Within Data Science, this role sits in Claims, supporting the function and the broader ambition to automate more of the claims journey. Claims is one of Marshmallow's most important customer touchpoints, and we're looking for a Senior Data Scientist who can provide technical expertise across traditional ML and Generative AI, bring system-level thinking to how we scale decisioning, and confidently challenge proposals to ensure we build robust, sustainable solutions. WHAT YOU'LL BE DOING * Build and iterate on multimodal AI models that reduce claims cost and improve claims processing, including models that analyse emails, documents, and claim summaries for operational teams * Develop machine learning models that support claims automation, including use cases such as negotiation strategies, litigation strategies, and total loss prediction * Explore and evaluate new data sources that could improve model performance and decision-making, such as fraud signals, open banking, and telematics data * Design and build agentic AI solutions to automate and streamline claims workflows * Collaborate closely with Product, Data, and Engineering teams to test hypotheses, develop new features, and turn ideas into production-ready solutions * Work with the MLOps team to improve data science and AI model infrastructure, including deployment, monitoring, evaluation, and feedback loops * Help define the right technical approach for problems, balancing speed, quality, and scalability while ensuring solutions are practical for the business * Set a strong standard for experimentation, measurement, and model performance, helping the team understand impact, uncertainty, and trade-offs clearly WHO YOU ARE * You think in systems: you can connect the dots between data science, engineering, and product to shape scalable solutions that build on each other over time. * You're confident in challenging assumptions and pushing for the right approach, using strong communication skills to influence stakeholders across seniority levels and disciplines with clear, pragmatic reasoning. * You thrive in ambiguity and change, staying resilient and effective during transitions while bringing structure, clarity, and momentum to complex problem spaces. * You're motivated by real-world impact, partnering closely with cross-functional teams to drive meaningful automation and better customer outcomes across the claims journey. WHAT YOU'LL BRING * Strong commercial experience delivering end-to-end machine learning solutions, from problem framing and experimentation through to production deployment and ongoing monitoring * Hands-on experience building and shipping production AI or machine learning systems, including evaluation, quality considerations, and integration into operational workflows * Experience working on applied problems involving structured and unstructured data, with an interest in multimodal modelling and AI systems * A strong statistical and modelling foundation, with experience working on risk-based decisioning or other complex, uncertain problem domains * Proven ability to work cross-functionally with Product, Engineering, Operations, and MLOps to deliver scalable solutions * Strong communication and stakeholder management skills, with confidence in discussing trade-offs and pushing back constructively when needed PERKS OF THE JOB * Bonus scheme designed to reward high performance * Private medical insurance with Vitality, mental health support with Oliva * Personal learning budget and 2 dedicated L&D days a year * Monthly flexible benefits budget to spend as you choose * 25 days holiday plus bank holidays * 4 weeks Work From Anywhere per year We are able to offer visa sponsorship for this position. OUR PROCESS * Initial call with a member from our Talent Team (30 mins) * Past Experience interview with Hiring Manager (60 mins) * Technical interview with a couple of the team (90 mins) * Culture interview (60 mins) Diversity of thought We know the best ideas come from having different perspectives in the room - and we're committed to hiring fairly, regardless of background, identity or experience. If you see yourself in this role, we'd encourage you to apply.