Want to know if this job is worth applying to?
Greater London, England, United Kingdom
Hybrid
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.
