The way people discover and book holidays is changing, and we’re rebuilding our technology for what comes next.
We are Awaze, Europe’s largest managed vacation rentals and holiday resorts business, bringing together some of the continent’s most recognised travel brands, including cottages.com, Hoseasons, NOVASOL and James Villa Holidays.
With more than 1.5 million bookings every year, 100,000+ properties and customers across Europe, we already operate at serious scale. But the next chapter for Awaze is about much more than scale.
We’re embarking on an ambitious AI transformation that will reshape how our customers discover, plan and book their holidays, and how our engineering teams build the technology behind those experiences.
Our strategy spans AI-powered search, natural-language discovery, intelligent recommendations, richer property data and AI-assisted engineering, all underpinned by a platform built around speed, trust, quality and real-time data.
Position: Data Scientist
We’re looking for an exceptional product-minded Data Scientist who can build and operate warehouse-based ML pipelines, design decision-relevant metrics and experiments, and reason about ranking well enough to decide what should be modelled, monitored and changed.
The role will extend Awaze’s existing sort-order capability: training tabular propensity models; combining their outputs with commercial and customer criteria through multi-criteria scoring; tuning and evaluating criteria and weights; and designing reliable ranking outputs for Search and other customer surfaces.
This is primarily a Data Science role rather than a pure ML Engineering role. Strong engineering practice is essential, but the differentiator is the ability to connect models, experiments and business decisions: formulate hypotheses, distinguish prediction from causal impact, understand interactions between ranking, price, promotion and channel decisions, and turn evidence into a product recommendation.
The data scientist will also own work beyond initial delivery: stakeholder discovery, roadmap shaping, experiment readouts, production monitoring, documentation, mentoring and knowledge transfer.
A bit more about what you’ll be doing:
Building intelligent ranking and recommendation capabilities
- Develop, improve and operate Machine Learning models that predict customer preferences, propensity to book and property relevance.
- Evolve our existing ranking capability using Python, CatBoost, optimisation techniques and multi-criteria decision-making.
- Explore more advanced ranking approaches, including personalised search, destination-specific ranking and recommendation systems.
- Balance multiple commercial and customer objectives, including conversion, relevance, pricing, margin and inventory exposure.
- Design reliable ML pipelines and ensure model outputs can be effectively integrated into customer-facing products.
Driving experimentation and commercial impact
- Design and run A/B tests to understand how ranking changes influence customer behaviour and business outcomes.
- Partner with Product and Commercial teams to define hypotheses, success metrics and measurable business opportunities.
- Apply statistical reasoning and causal thinking to distinguish correlation, predictive performance and genuine incremental impact.
- Evaluate trade-offs between ranking, pricing, promotions, inventory and marketing decisions.
- Translate complex analytical findings into clear, actionable recommendations that influence product and commercial strategy.
Building scalable, production-ready Data Science
- Build and maintain end-to-end ML pipelines using Python, SQL, Snowflake and AWS.
- Establish robust model evaluation, monitoring, alerting and retraining processes.
- Develop reporting tools and dashboards that provide visibility into model performance and commercial outcomes.
- Apply strong engineering practices across version control, testing, documentation and production deployment.
- Improve existing systems pragmatically while laying the foundations for more advanced capabilities.
Who We’re Looking For:
We’re looking for someone who combines strong applied Data Science expertise with commercial curiosity, product thinking and the ability to turn insight into action.
You’ll ideally bring:
- Strong hands-on experience developing and deploying Machine Learning models using Python.
- Advanced SQL skills and experience with Snowflake or another modern cloud data platform.
- Experience implementing and evaluating ranking models, recommendation systems or optimisation solutions.
- Exposure to search relevance, learning-to-rank, recommender systems or personalisation.
- A strong understanding of A/B testing, statistical experimentation, hypothesis testing and causal reasoning.
- Experience designing meaningful product and commercial metrics, including guardrails and experiment success measures.
- Knowledge of multi-criteria optimisation, weighted scoring or similar decision-making approaches.
- Experience building and operating production ML pipelines, including monitoring, retraining and model evaluation.
- Strong software engineering practices, including Git, testing and documentation.
- Experience building dashboards and analytical applications using Streamlit or similar tools.
- The ability to translate ambiguous commercial challenges into structured analytical problems and practical solutions.
- Confidence working with Product Managers, Engineers and senior commercial stakeholders.
What will we offer you?
- Annual Bonus Scheme
- 25 days holidays (plus the option to buy an unlimited number of additional days)
- Holiday Discounts (across all AWAZE brands)
- Personal training allowance via Sunlight
- Hybrid working (we work 2 days in our Manchester office every week, with 3 days working from home)
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