Senior Applied ML Scientist

hackajob is collaborating with Nory to connect them with exceptional tech professionals for this role.

Let’s fix hospitality, for good.

We’re on a mission to help the hospitality industry double their profitability, reduce their carbon footprint, and create better working environments for their teams.

Our CEO, Conor, founded and scaled Mad Egg - one of the fastest-growing restaurant groups in Ireland. After years of juggling “market-leading” systems, spreadsheets, and paper printouts, he set out to build the solution he wished he had from day one: Nory.

Nory is an all-knowing restaurant management system. It combines real-time data with AI predictive analytics to help restaurants operate with consistency, certainty and profitability. From food prep to forecasting, Nory puts operators in control of their margins.

Now, with demand growing faster than we imagined - and a recent Series A led by Accel - we’re scaling fast. We’ve grown to a team of 50+ across Ireland, the UK and Spain, and we’re just getting started.

We’re now looking for a Senior Applied ML Scientist to join our Data team. This role is ideal for a senior independent doer — someone who has repeatedly owned ML systems end-to-end, applied strong classical ML/statistical reasoning, and delivered models that make or save money in the real world.

This is not a research or experimentation role. It’s about building pragmatic ML systems that drive KPIs - forecasting, optimisation, regression, and classification - and ensuring those systems keep working in production.

• Own the full ML lifecycle: from business problem formulation and algorithm design through to deployment, monitoring, and iteration in production
• Apply strong classical ML thinking: regression, time series forecasting, classification, optimisation, clustering - picking the right tool and justifying why
• Keep models alive: build monitoring into every deployment (drift detection, retraining, KPI tracking) so models keep delivering value in production
• Collaborate deeply with squads: work alongside product managers, engineers, and designers to define KPIs, design data flows, and embed ML into product features
• Framework in business terms: focus on outcomes (profitability, efficiency, waste reduction), not just technical metrics
• Contribute to culture: share learnings, give feedback, and help raise the bar for applied ML at Nory
  
  

What you’ll bring

• Background: MSc/PhD in a stats-heavy STEM field (Applied Maths, Statistics, Physics, Econometrics)
• E2E ownership: You have 4+ years of experience taking ML systems from idea to production in a commercial setting, repeatedly and successfully. You’re confident in owning the process independently, from problem formulation to monitoring impact in production
• Classical ML theory depth: You are familiar with time-series forecasting, regression/classification, causal signals, feature engineering, evaluation/monitoring, and drift
• Technical Proficiency: Strong Python and experience with ML libraries (e.g., Scikitlearn, Pandas, LightGBM), plus working knowledge of cloud infrastructure and data tools (Snowflake, DBT, Omni)
• Rigour & Impact: You apply rigorous statistical and experimental thinking, and can demonstrate how your work has driven measurable business outcomes
• Collaboration: You thrive in highly collaborative environments, communicate clearly, and offer help where needed to improve team outcomes
• Startup mindset: You thrive in fast-paced environments, move quickly, and take initiative to maintain momentum and resolve issues efficiently. You are comfortable with ambiguity and multitask effectively while delivering real impact
  
  

Nice-to-have

• Experience in smaller data teams with high ownership cultures
• Exposure to B2B SaaS products
• Familiarity with LLMs - useful, but this role is not for LLM specialists