At a Glance
- Tasks: Transform guest data into real-time risk scores and detect fraud for short-term rentals.
- Company: Join a pioneering startup revolutionising guest verification and damage protection.
- Benefits: Part-time role with potential for full-time, equity options, and hands-on experience.
- Other info: Work closely with the co-founder and shape the future of our data strategy.
- Why this job: Be a founding data scientist and make a real impact in a growing company.
- Qualifications: 3+ years in ML models, strong stats background, and experience in fraud/risk.
The predicted salary is between 30000 - 40000 £ per year.
We're bringing on our first Data Scientist — starting part-time, with a clear path to full-time as we grow. Safeguest is a guest verification and damage protection platform for short-term rental hosts. We help hosts and property managers screen guests, score risk in real time, and offer damage protection and deposit-waiver products that replace traditional security deposits. Our risk engine sits at the center of every booking decision and every product we price — and we're looking for the person who'll make it world-class.
This is a founding data role, structured to start as a focused part-time engagement (≈2–3 days/week). You'll deliver real, measurable wins in your first 90 days — and we expect this to grow into a full-time seat for the right person.
What you'll own:
- Guest risk scoring — turn verification, booking, and behavioral signals into real-time risk scores that beat our current rules
- Fraud detection — catch fake IDs, stolen cards, and bad actors before check-in, without blocking good guests
- Actuarial pricing — model claim frequency and severity to keep our protection products profitable
You'll work directly with the co-founder, build our data and modeling foundations from scratch, and ship models that measurably reduce losses.
You're a great fit if you have:
- 3+ years building and deploying ML models in production
- Strong grounding in statistics and probability
- Hands-on experience in fraud/risk, credit/underwriting, or actuarial/insurance pricing
- Comfort with messy, imbalanced, real-world data
- A pragmatic, ownership-driven mindset — you scope, prioritize, and ship
Bonus points for: insurtech / fintech / payments background, MLOps experience, or short-term rental / marketplace domain knowledge.
Why this setup: Starting part-time lets us move fast together and prove the impact — with founding-team equity and a genuine path to full-time as the role grows.
Interested, or know someone who'd be perfect? Drop a comment or DM me.
Tech Data Scientist employer: Safeguest
At Safeguest, we pride ourselves on being an innovative employer that values growth and collaboration. As a part-time Tech Data Scientist, you'll have the unique opportunity to shape our data foundations while working closely with our co-founder in a dynamic startup environment. We offer a clear path to full-time employment, competitive equity options, and a culture that encourages ownership and impactful contributions from day one.
StudySmarter Expert Advice🤫
We think this is how you could land Tech Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the insurtech and data science communities. Attend meetups, webinars, or even just grab a coffee with someone in the field. You never know who might have a lead on that perfect part-time gig!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML models and any relevant projects. This is your chance to demonstrate how you can turn messy data into actionable insights, which is exactly what Safeguest needs.
✨Tip Number 3
Tailor your approach! When reaching out to Safeguest, highlight your experience with fraud detection and risk scoring. Make it clear how your background aligns with their mission to enhance guest verification and damage protection.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the Safeguest journey from the ground up.
We think you need these skills to ace Tech Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Tech Data Scientist. Highlight your experience with ML models, fraud detection, and any relevant stats knowledge. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data science and how you can contribute to Safeguest's mission. Be sure to mention any specific projects or experiences that relate to guest risk scoring or actuarial pricing.
Show Your Work:If you've got examples of your work, like projects or case studies, don’t hesitate to include them! We love seeing how you've tackled real-world data challenges and delivered measurable results.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get noticed by the right people. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at Safeguest
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning models and statistical methods. Be ready to discuss your past projects, especially those involving fraud detection or risk scoring, as these are key for the role.
✨Understand the Company’s Mission
Dive into Safeguest's platform and understand how they operate. Familiarise yourself with guest verification and damage protection processes. Showing that you get their mission will impress them and demonstrate your genuine interest.
✨Prepare for Real-World Scenarios
Think about how you would handle messy, imbalanced data in real-world situations. Be prepared to discuss specific examples from your experience where you successfully tackled similar challenges.
✨Show Your Ownership Mindset
This role is all about taking initiative. Be ready to share instances where you scoped, prioritised, and delivered projects. Highlight your ability to work independently and drive results, as this aligns perfectly with their expectations.
