loveholidays
Data Scientist

How your CV stacks up
Upload your CV to see how well it fits this job role
?%
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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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 deep dive 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


Get help with your application
Your very own career expert that helps elevate your application to the next level.
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.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Location