loveholidays Logo

loveholidays

Data Scientist

Reposted 23 Days Ago
Be an Early Applicant
Hybrid
London, Greater London, England, GBR
Entry level
Hybrid
London, Greater London, England, GBR
Entry level
Develop and improve machine learning products for pricing, recommendations, and other business areas. Translate ambiguous business problems into practical models, experiments, and evaluations; collaborate with engineering, product, and analytics teams to deploy and monitor production models; investigate performance changes; and communicate insights to support evidence-based commercial decisions.
The summary above was generated by AI

Why loveholidays?

We’re on a mission to open the world to everyone, giving our customers unlimited choice, unmatched ease and unmissable value for their next getaway.

Our trailblaze together culture is what drives our success, powered by our people and the way they work. Using progressive technology, we drive cutting-edge innovation and improve how our customers discover, book and experience their holidays. You’ll have the opportunity to accelerate your growth through meaningful challenges, new experiences and the freedom to shape your own path. You’ll create impact for our future by taking ownership, contributing to shared goals and helping shape what comes next, all as part of our enhanced international community of talented, collaborative and passionate teams.

The difference you’ll make

You’ll sit in the Data Science team, reporting to the Head of Data Science. You’ll work closely with Product and Engineering teams to develop predictive models for pricing, recommendations, and other business domains. Together, the team will leverage data to build statistical models that improve commercial decisions.

Data Science sits within our Platform function, which builds the technology and shared capabilities that power the loveholidays experience. By creating scalable products, systems and tools, Platform helps the wider organisation move faster, work more independently and deliver better outcomes for customers.

Your day-to-day:

  • Build and improve data science products across pricing, recommendations and other business domains to improve customer experiences and commercial outcomes.

  • Turn ambiguous business problems into practical data science solutions, from exploration and modelling through to experimentation and evaluation.

  • Partner with engineers, analysts and product teams to deploy reliable models and embed recommendations into everyday decision-making.

  • Monitor model performance, investigate changes and continuously improve solutions as customer behaviour and business needs evolve.

  • Communicate findings clearly, challenge assumptions and help teams make confident, evidence-based decisions.

Your skillset:

  • Strong experience developing and delivering practical machine learning solutions, balancing model performance, business value and long-term maintainability.

  • Proficiency in Python and SQL, with experience working with large, complex datasets.

  • A solid grounding in statistics, experimentation and machine learning, including model evaluation and causal thinking.

  • Experience collaborating with engineers to deploy, monitor and improve models in production.

  • Strong communication skills, with the ability to explain technical concepts and influence product and commercial decisions.

The interview journey:

  • Intro with a member of our Talent Acquisition team - 30 minutes

  • 1st Stage: Virtual Interview with Hiring Manager - 45 minutes

  • 2nd Stage: Two on-site interviews

    • 50 minutes for a project discussion deepdive with member(s) of the Data Science team

    • 1 hour technical discussion around a case study with member(s) of the Data Science team

  • Final-stage: Virtual interview with key stakeholders - 45 minutes

Perks of joining us:

  • Company pension contributions at 5%

  • Individualised training budget for you to learn on the job and level yourself up

  • Discounted holidays for you, your family and friends

  • 25 days of holidays per annum (plus 8 public holidays) increases by 1 day for every second year of service, up to a maximum 30 days per annum

  • Ability to buy and sell annual leave

  • Access to our electric vehicle salary sacrifice scheme

  • Cycle to work scheme, season ticket loan and eye care vouchers

 

Our commitment to inclusion

At loveholidays, we focus on creating an inclusive environment where everyone can contribute, grow and succeed. We value the different perspectives, experiences and ideas each person brings, because they help us work better together, challenge our thinking and make stronger decisions.

As we continue to grow and evolve, we want everyone to feel supported and able to do their best work. We’re also committed to making our hiring process accessible, so please let our Talent Acquisition team know if you need any adjustments at any stage.

 
HQ

loveholidays Fulham, England Office

Fulham, United Kingdom

loveholidays London, England Office

3 Shortlands, West Kensington, London, United Kingdom, W6 8DA

Similar Jobs

9 Days Ago
Hybrid
London, England, GBR
Senior level
Senior level
Artificial Intelligence • Fintech • Payments • Business Intelligence • Financial Services • Generative AI
Lead strategic and operational data science through quantitative analysis, forecasting, experimentation, and data storytelling. Mentor data scientists, advise cross-functional leaders, define metrics and forecasts, and build scalable decision-support systems. The role also contributes to AI and machine-learning systems that optimize product behavior, pricing, risk, allocation, and customer experiences, with an emphasis on rigorous validation, governance, and measurable outcomes.
Top Skills: Ai AnalyticsData MiningForecastingMachine LearningPythonRSQL
13 Days Ago
Hybrid
London, Greater London, England, GBR
Entry level
Entry level
Fintech • Payments • Financial Services
Develop and support credit risk and pricing models for lending products. Responsibilities include data exploration, feature engineering, statistical analysis, model monitoring, deployment support, documentation, and collaboration with Credit Strategy, Product, Engineering, and Data Engineering teams. The role is designed for an early-career data scientist with strong quantitative skills and an interest in credit and financial services.
Top Skills: Machine LearningPythonSQL
21 Days Ago
Hybrid
London, Greater London, England, GBR
Senior level
Senior level
Financial Services
Build scalable LLM-powered investment tools and AI workflows, including RAG, context management, data pipelines, model integrations, evaluation, and observability. Partner with investment and research teams to translate financial processes into secure enterprise solutions. Apply machine learning, statistical methods, Python, SQL, and financial-market knowledge in a regulated environment while optimizing AI quality, cost, latency, reliability, and business impact.
Top Skills: Arize PhoenixLanggraphLangsmithLlamaindexModel Context Protocol (Mcp)OpeninferenceOpentelemetryPythonSemantic KernelSQL

What you need to know about the London Tech Scene

London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account