At a Glance
- Tasks: Design datasets and develop NLP models to secure AI tools for enterprises.
- Company: Join a VC-backed AI security startup with top-tier investors.
- Benefits: Competitive salary, innovative work environment, and opportunities for growth.
- Other info: Dynamic startup culture that encourages innovation and collaboration.
- Why this job: Make a real impact in AI security while working with cutting-edge technology.
- Qualifications: Expert Python skills and experience in shipping production-grade models.
The predicted salary is between 60000 - 80000 £ per year.
VC-backed AI security startup funded by Ten Eleven Ventures and In‑Q‑Tel.
You will be a critical member of the product delivery team, laying the groundwork for secure Generative AI adoption in the enterprise. You'll design curated datasets, build detection models for sensitive data, and iterate based on real‑world customer feedback to ensure teams can use AI tools safely and confidently.
Location: London, UK
Why this role is remarkable:
- Work at the forefront of AI security with a team led by cybersecurity experts and backed by top‑tier investors like Ten Eleven Ventures and In‑Q‑Tel.
- Direct impact on a category‑defining product that enables safe enterprise adoption of LLMs by protecting sensitive data in real‑time.
- Join an AI‑first culture where you are encouraged to use and build with the latest tools like Claude Code and Cursor to automate workflows.
What You Will Do:
- Design and curate comprehensive datasets tailored for training and fine‑tuning sensitive data detection models.
- Develop, validate, and ship production‑ready NLP models that categorize and protect enterprise data at scale.
- Drive continuous model improvement by analyzing performance dashboards and incorporating direct feedback from customer interactions.
Ideal Candidate:
- Proven track record of shipping production‑grade models and managing high‑quality datasets within a live SaaS product environment.
- Expert‑level Python skills with deep knowledge of NLP techniques, classification approaches, and data categorization taxonomies.
- A product‑driven mindset that prioritises incremental delivery and thrives in a fast‑paced, innovative startup atmosphere.
Data Scientist at VC-backed AI security startup in London employer: Jack & Jill
Join a dynamic VC-backed AI security startup in London, where you will be at the cutting edge of technology, working alongside cybersecurity experts to shape the future of secure Generative AI. Our collaborative and innovative work culture fosters personal growth and encourages the use of the latest tools, ensuring that you have the resources to make a meaningful impact on enterprise data protection. With a focus on employee development and a commitment to creating a safe and inclusive environment, this is an exceptional opportunity for those looking to thrive in a fast-paced startup setting.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist at VC-backed AI security startup in London
✨Tip Number 1
Network like a pro! Reach out to people in the AI and cybersecurity space on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational interviews. You never know who might have a lead on that Data Scientist role!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving NLP and data categorisation. Use platforms like GitHub to share your code and demonstrate your expertise. This will make you stand out when applying through our website.
✨Tip Number 3
Prepare for the interview by brushing up on your Python and NLP knowledge. Be ready to discuss your past projects and how you've iterated based on feedback. Practice common data science interview questions to boost your confidence!
✨Tip Number 4
Follow up after interviews! A quick thank-you email can go a long way. Mention something specific from your conversation to remind them of your fit for the role. It shows you're genuinely interested and keeps you top of mind!
We think you need these skills to ace Data Scientist at VC-backed AI security startup in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Data Scientist. Highlight your experience with NLP models and dataset management, and don’t forget to mention any relevant projects that showcase your skills in a SaaS environment.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI security and how your background makes you a perfect fit for our team. Be sure to mention specific tools or techniques you’ve used that align with what we do.
Showcase Your Projects:If you’ve worked on any cool projects related to data categorization or model development, make sure to include them. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it gets into the right hands!
How to prepare for a job interview at Jack & Jill
✨Know Your Data Inside Out
Make sure you’re well-versed in the datasets you’ve worked with. Be ready to discuss how you designed and curated them, as well as the challenges you faced. This will show your depth of knowledge and your ability to handle sensitive data.
✨Showcase Your NLP Expertise
Prepare to talk about your experience with NLP models. Bring examples of production-grade models you've shipped and be ready to explain the techniques you used. This is your chance to demonstrate your expert-level Python skills and classification approaches.
✨Emphasise Continuous Improvement
Highlight your approach to model improvement. Discuss how you analyse performance dashboards and incorporate customer feedback. This shows that you’re not just about building models but also about refining them based on real-world use.
✨Fit into the Startup Culture
Research the company’s culture and be prepared to discuss how you thrive in fast-paced environments. Share examples of how you’ve delivered incrementally in previous roles, which aligns with their product-driven mindset.
