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- Tasks: Evaluate dialogue across text and audio, ensuring top-notch data labelling.
- Company: Join Yellowcat, a dynamic team in Central London.
- Benefits: Earn £140 daily plus holiday pay, with weekly payments.
- Other info: On-site role, perfect for those seeking hands-on experience.
- Why this job: Make an impact in AI while honing your analytical skills.
- Qualifications: Fluency in Dutch and strong analytical abilities required.
The predicted salary is between 36400 - 36400 £ per year.
Yellowcat in Greater London is seeking Dutch speaking Researchers / Administrators for a 6-month temporary position. The role involves evaluating dialogue on multiple data types including text and audio, delivering high-quality labelling to meet KPIs, and diagnosing operational issues.
Fluency in Dutch and strong analytical skills are essential. The position requires on-site work 5 days a week with a daily rate of £140 plus holiday allowance, paid weekly through PAYE.
Dutch ML Data Labeler – AI Project (6m, Central London) employer: Yellowcat
Contact Detail:
Yellowcat Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Dutch ML Data Labeler – AI Project (6m, Central London)
✨Tip Number 1
Get to know the company! Research Yellowcat and their projects. Understanding their values and goals will help you tailor your approach during interviews and show that you're genuinely interested.
✨Tip Number 2
Practice makes perfect! Brush up on your Dutch language skills and analytical abilities. You might be asked to demonstrate these during the interview, so being prepared can really set you apart.
✨Tip Number 3
Network like a pro! Connect with current or former employees on LinkedIn. They can provide insider tips about the interview process and what it’s like to work at Yellowcat.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for passionate individuals who want to make an impact in the AI space.
We think you need these skills to ace Dutch ML Data Labeler – AI Project (6m, Central London)
Some tips for your application 🫡
Show Off Your Dutch Skills: Since fluency in Dutch is a must, make sure to highlight your language skills right at the top of your application. We want to see how well you can communicate in Dutch, so don’t hold back!
Demonstrate Your Analytical Prowess: This role needs strong analytical skills, so include examples from your past experiences where you've successfully evaluated data or solved problems. We love seeing how you think!
Tailor Your Application: Make your application stand out by tailoring it to the job description. Use keywords from the listing and show us how your experience aligns with the role. We appreciate a personal touch!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss any important updates from us!
How to prepare for a job interview at Yellowcat
✨Brush Up on Your Dutch
Since fluency in Dutch is a must for this role, make sure you’re comfortable speaking and writing in the language. Practise common phrases and technical vocabulary related to data labelling and AI to show your proficiency during the interview.
✨Know Your Data Types
Familiarise yourself with different data types, especially text and audio, as they are crucial for the role. Be prepared to discuss how you would evaluate and label these data types effectively, and think of examples from your past experiences.
✨Demonstrate Your Analytical Skills
Highlight your analytical skills by preparing to discuss specific instances where you diagnosed operational issues or improved processes. Use the STAR method (Situation, Task, Action, Result) to structure your answers clearly and effectively.
✨Understand the KPIs
Research what key performance indicators (KPIs) might be relevant for a data labelling role. Be ready to talk about how you would meet these KPIs and why they are important for the success of the project. This shows that you’re not just focused on the task but also on the bigger picture.