Let’s fix hospitality, for good.
Hospitality is tough – margins are thin, waste is high, and teams are stretched. But it doesn’t have to be this hard. That’s why we built Nory.
Our CEO, Conor, knows the pain first-hand. After founding and scaling Mad Egg in Ireland, he got fed up with juggling “market-leading” systems, clunky spreadsheets, and endless printouts. So he set out to build the tool he wished he’d had from day one.
Nory is an all-knowing restaurant management system. It blends real-time data with AI predictive analytics, giving operators control of their margins. From food prep to forecasting, it’s operational intelligence that helps restaurants run with consistency, certainty, and profit. The result? Thriving restaurants, better jobs, less waste, healthier margins. Learn more about what we are building here.
And we’re just getting started. Fresh off a Series B led by Kinnevik, we’ve grown to 80+ people across Ireland, the UK, Spain and New York – and demand is scaling faster than we ever imagined.
We’re looking for a Senior Data Scientist – Applied Machine Learning to design, build, and scale machine learning systems that directly power operational decisions across thousands of restaurant shifts every week. This is not a research-only role. And it’s not about models that live in notebooks.
It’s about building production-grade ML systems that improve margins – and making sure they keep delivering value long after deployment. Read more about what it’s like being a Data Scientist at Nory here.
As a Senior Data Scientist – Applied Machine Learning at Nory, you’ll build and scale production-grade ML systems that power margin-critical decisions across forecasting, labour planning, and operational optimisation – turning live real-world restaurant data into measurable profit improvement.
Own ML systems end-to-end, from problem framing and data design through to deployment, monitoring, and iteration in production.
Build reliable, production-grade ML services, working close to APIs, pipelines, and cloud infrastructure to ensure models are robust, observable, and maintainable.
Improve operational performance through measurable impact, increasing forecast accuracy, automation rates, and margin contribution – not just model metrics.
Design monitoring and drift strategies from day one, ensuring models stay accurate, stable, and commercially valuable over time.
Apply rigorous statistical thinking, choosing the right level of complexity and running sound experiments to support clear go / no-go decisions.
Partner closely with Product, Engineering, and Commercial teams, embedding ML into live workflows that operators trust and rely on daily.
Raise the bar for applied ML at Nory, influencing standards, reviewing work, mentoring others, and strengthening our systems thinking as we scale.
Proven ownership of production ML systems, having taken models from ambiguous problem to deployed, monitored, revenue-impacting capability.
Strong statistical foundations, with an MSc, PhD, or equivalent depth in applied statistics, experimentation, and quantitative reasoning.
Production-first mindset, comfortable working close to APIs, CI/CD, cloud infrastructure, and modern data tooling.
Depth in classical machine learning, including forecasting, regression, classification, feature engineering, and drift detection – with the judgement to choose the right level of complexity.
Experience measuring real business impact, thinking in terms of automation rates, cost reduction, accuracy uplift, and margin improvement.
Clean, maintainable Python skills, writing code suitable for shared codebases rather than notebooks alone.
Systems thinking, understanding how models interact with data pipelines, product workflows, and operational edge cases.
Clear communication skills, able to explain trade-offs and influence engineers, PMs, and senior stakeholders.
Startup ownership mentality, proactive, pragmatic, and comfortable operating with autonomy in a fast-scaling environment.
Nice-to-have:
Experience in B2B SaaS or operational domains such as logistics, workforce planning, supply chain, or forecasting-heavy environments.
Experience in lean, high-ownership data teams.
If you’re excited by what we’re building, we’d love to hear from you, even if you don’t tick every box.
🌎 Remote-first working environment - please note you must have the right to work in the UK/EU without sponsorship to be considered for this role
💰 Competitive salary range depending on experience
📈 Meaningful equity, at Nory everyone is an owner!
🌴 35 days of paid leave per year (including bank holidays)
🏥 Comprehensive private health insurance via Irish Life (Ireland) and Axa (UK)
🍼 Enhanced parental leave and baby loss support
📚 Learning & development culture – €1000 personal annual budget + quarterly book budget
🖥️ €250 home office workspace budget
🥳 Regular team offsites & socials
✈️ Work from anywhere for up to 3 months of the year
📍Offices in either London 🇬🇧 , Dublin 🇮🇪 or Spain 🇪🇸
👏 And much more
Our vision is to build a better future for the restaurant industry.
One where operators are in control, margins are stronger, and frontline teams can build careers they’re proud of. To get there, we move fast, stay focused, and hold ourselves to a high bar. Our values guide how we work, grow, and win – together.
These are the values we live by:
We serve up impact with a side of profit: We prioritise work that delivers real financial results for our restaurant partners.
We prioritise speed of service: We move fast, unblock quickly, and deliver with urgency.
We act like owners: We own problems, raise the bar, and build better every day.
We win as a crew: We grow stronger through feedback, collaboration, and shared wins.
At Nory, we believe that diverse teams build better products. We welcome applicants from all backgrounds, identities, and walks of life. We do not discriminate based on gender, ethnicity, sexual orientation, religion, family status, age, disability, or race. What matters to us is how you think, how you work, and what you bring to the table. Please let us know if you require any adjustments so you can bring your best self to the interview process.