At a Glance
- Tasks: Transform guest data into real-time risk scores and detect fraud for short-term rentals.
- Company: Join Safeguest, a pioneering platform in 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 startup.
- Qualifications: 3+ years in ML models, strong stats background, and experience in fraud detection.
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.
Data scientist (marketing) employer: Safeguest
At Safeguest, we pride ourselves on being an innovative employer that values growth and collaboration. As a founding Data Scientist, you'll have the unique opportunity to shape our data strategy while working closely with our co-founder in a dynamic startup environment. We offer flexible part-time hours with a clear pathway 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 Data scientist (marketing)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to fraud detection or risk scoring. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your statistics and probability knowledge. Be ready to discuss how you've tackled messy data in the past and how you can apply that to Safeguest's needs.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at Safeguest.
We think you need these skills to ace Data scientist (marketing)
Some tips for your application 🫡
Show Your Passion for Data:When you're writing your application, let your enthusiasm for data science shine through! We want to see how excited you are about building and deploying ML models, especially in the context of fraud detection and risk scoring.
Tailor Your Experience:Make sure to highlight your relevant experience in your application. If you've worked with messy, real-world data or have a background in insurtech or fintech, shout about it! We love seeing how your skills align with what we're looking for.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and make sure your key achievements stand out. Remember, we’re looking for measurable wins, so share those!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to keep track of your application and ensures you don’t miss any important updates. Plus, we love seeing applications come directly from our site!
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 how you've built and deployed models in production, especially in fraud detection or risk scoring. They’ll want to see your hands-on experience, so prepare some examples!
✨Understand the Business
Get familiar with Safeguest's platform and how they operate in the short-term rental market. Knowing their guest verification process and damage protection products will show that you're genuinely interested and can contribute to their goals right from the start.
✨Prepare for Real-World Scenarios
Think about how you would handle messy, imbalanced data in real-world situations. Be ready to discuss specific challenges you've faced and how you overcame them. This will demonstrate your pragmatic mindset and ownership-driven approach.
✨Show Your Passion for Growth
Since this role starts part-time with a path to full-time, express your enthusiasm for growing with the company. Talk about your long-term vision and how you see yourself contributing to building their data and modelling foundations from scratch.
