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- Tasks: Develop and evaluate generative models through manual and automatic assessments.
- Company: Leading recruitment agency in Greater London with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for skill development.
- Why this job: Join a dynamic team and shape the future of AI technology.
- Qualifications: Associate's degree in STEM and basic knowledge of Python, Unix, and SQL required.
- Other info: Collaborative environment with strong emphasis on communication and problem-solving.
The predicted salary is between 36000 - 60000 £ per year.
A leading recruitment agency is looking for additional data analysts in Greater London, focused on developing manual and automatic evaluations for generative models.
Responsibilities include:
- Prototyping evaluation protocols
- Conducting in-house ratings
- Collaborating with engineers to identify model gaps
Candidates should have an Associate's degree in a STEM field and basic knowledge of Python, Unix, and SQL. Strong communication and problem-solving skills are essential for this role.
AI Evaluation Analyst - Quality Metrics & Data in London employer: Morgan McKinley
Contact Detail:
Morgan McKinley Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Evaluation Analyst - Quality Metrics & Data in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, or join online forums. The more connections we make, the better our chances of landing that AI Evaluation Analyst gig.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with Python, SQL, and any evaluation protocols you've developed. This will help us stand out when chatting with potential employers.
✨Tip Number 3
Practice makes perfect! Prepare for interviews by simulating common questions related to data analysis and problem-solving. We can even do mock interviews together to boost our confidence.
✨Tip Number 4
Apply through our website! It’s super easy and gives us a direct line to the hiring team. Plus, we can tailor our applications to highlight our strengths in quality metrics and data analysis.
We think you need these skills to ace AI Evaluation Analyst - Quality Metrics & Data in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant skills and experiences that match the job description. We want to see how your background in STEM and any experience with Python, Unix, or SQL can shine through!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you're the perfect fit for the AI Evaluation Analyst role. Share specific examples of your problem-solving skills and any projects where you've developed evaluation protocols.
Show Off Your Communication Skills: Since strong communication is key for this role, make sure your application reflects that. Use clear and concise language, and don’t hesitate to showcase any collaborative projects you’ve worked on with engineers or teams.
Apply Through Our Website: We encourage you to apply directly through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Morgan McKinley
✨Know Your Tech
Brush up on your Python, Unix, and SQL skills before the interview. Be ready to discuss how you've used these tools in past projects or coursework. This will show that you’re not just familiar with the basics but can apply them effectively.
✨Understand Evaluation Protocols
Familiarise yourself with both manual and automatic evaluation methods for generative models. Be prepared to talk about any relevant experience you have prototyping evaluation protocols or conducting ratings, as this will demonstrate your hands-on knowledge.
✨Communicate Clearly
Strong communication skills are a must for this role. Practice explaining complex concepts in simple terms, as you may need to collaborate with engineers. Think of examples where you successfully communicated technical information to non-technical audiences.
✨Problem-Solving Mindset
Prepare to showcase your problem-solving skills. Think of specific challenges you've faced in data analysis and how you approached them. This will help illustrate your analytical thinking and ability to identify model gaps, which is crucial for the role.
