Dish’d is the UK’s fastest-growing franchisor of virtual food brands. We partner with food operators to help them maximise their kitchen capacity by launching and scaling delivery-only brands across the UK.
We’re looking for a commercially minded Data Scientist to design and build predictive models that directly shape expansion, pricing, and operational decisions across a fast-growing, multi-brand food platform. This is not a reporting role. This is a modelling role.
You will build forecasting systems from scratch, own experimentation frameworks, and influence real commercial strategy — from new site openings to pricing optimisation and franchise performance.
The Role
Forecasting & Predictive Modelling (Core Focus)
You will design and deploy predictive models that directly support growth and profitability, including:
-
Sales forecasting models for new site openings, brand placement, and territory expansion
-
Demand forecasting at brand, location, and time-of-day level
-
Pricing optimisation models to simulate revenue and margin impact
-
Churn prediction models to identify at-risk franchise partners
-
Customer lifetime value (CLV) and territory saturation analysis
-
Inventory and cost optimisation modelling
You’ll continuously refine and retrain models as new data becomes available, ensuring accuracy and commercial relevance over time.
Experimentation & Statistical Analysis
You will own our experimentation framework, including:
-
Designing A/B and multivariate testing for menus, pricing, and marketing
-
Geo-based experimentation across territories
-
Rigorous statistical evaluation of test results
-
Clear communication of findings with actionable recommendations
Automation & Operational Analytics
-
Build automated monitoring and anomaly detection systems
-
Integrate model outputs into dashboards and reporting workflows
-
Support development of data pipelines feeding model inputs
-
Evaluate and recommend AI-powered tools to improve forecasting accuracy
Collaboration & Commercial Impact
You’ll work closely with the Data Lead and Data Engineer to ensure models are built on clean, reliable warehouse data. You’ll also partner with Operations, Marketing, and Finance to translate business challenges into modelling opportunities — and communicate complex outputs in a clear, compelling way.
Your work will feed directly into commercial strategy and board-level reporting.
What We’re Looking For
Essential
-
3–5 years’ hands-on experience in applied data science or predictive analytics
-
Proven experience building forecasting models from scratch in a commercial environment
-
Strong Python skills (pandas, NumPy, scikit-learn, statsmodels, Prophet/NeuralProphet or similar)
-
Deep experience in time series forecasting (ARIMA, SARIMA, Prophet, exponential smoothing, gradient boosting approaches)
-
Experience building regression, classification, and clustering models
-
Strong statistical foundation (hypothesis testing, A/B testing, confidence intervals, causal inference)
-
Solid SQL skills
-
Experience taking models from prototype to production (validation, monitoring, iteration)
-
Excellent communication skills — able to translate complex outputs for non-technical stakeholders
-
Fluency in spoken and written English (IELTS Level 8 / Cambridge C2 equivalent)
-
Highly organised, detail-oriented, and self-motivated
Desirable
-
Experience with Power BI or similar BI tools
-
Familiarity with workflow automation tools (Airflow, n8n, etc.)
-
Cloud deployment experience (Azure, GCP, AWS)
-
NLP / sentiment analysis experience
-
Background in food delivery, QSR, logistics, or other fast-moving industries
-
Google Apps Script / Sheets automation
-
Git and collaborative development workflows
Why Join Us?
-
High commercial impact — your models will shape real expansion decisions
-
Direct exposure to strategic planning and senior leadership
-
Opportunity to build forecasting capability from the ground up
-
Clear pathway to Lead Data Scientist as the team scales
-
Fast-paced, high-growth environment where data drives decisions