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/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.
Data Marketing Scientist employer: Safeguest
At Safeguest, we pride ourselves on being an innovative employer that values growth and collaboration. As a part-time Data Marketing 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 Data Marketing 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 slide into DMs 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 ML models and any relevant projects. This is your chance to demonstrate your hands-on experience with messy data and fraud detection. Make it easy for potential employers to see what you can bring to the table.
✨Tip Number 3
Tailor your approach! When reaching out to Safeguest or similar companies, highlight your experience in risk scoring and actuarial pricing. Make it clear how your background aligns with their needs, especially in turning verification signals into actionable insights.
✨Tip Number 4
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 team. Don’t forget to follow up after applying; a little persistence goes a long way!
We think you need these skills to ace Data Marketing Scientist
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 fraud/risk or actuarial pricing. We’re looking for someone who can turn verification signals into real-time risk scores, so connect your past work to what we do at Safeguest.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and focus on what makes you a great fit for this role. Remember, we want to see your skills and how they align with our needs!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Safeguest
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of data Safeguest deals with. Brush up on guest verification processes, risk scoring, and fraud detection techniques. Being able to discuss how you would handle messy, imbalanced data will show that you understand the real-world challenges they face.
✨Showcase Your ML Experience
Prepare to talk about your experience building and deploying machine learning models. Have specific examples ready that demonstrate your ability to turn complex data into actionable insights, especially in fraud detection or actuarial pricing. This is your chance to shine!
✨Understand the Business Model
Familiarise yourself with Safeguest’s business model and how their risk engine impacts booking decisions. Knowing how to align your data strategies with their goals will set you apart as a candidate who can contribute from day one.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current challenges in risk scoring or how they envision the data team evolving. This not only demonstrates your enthusiasm but also helps you gauge if it’s the right fit for you.
