Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Review and refine AI-generated content while providing structured feedback.
- Company: Join a forward-thinking company focused on AI and data science.
- Benefits: Flexible part-time hours, remote work, and opportunities for skill development.
- Why this job: Make an impact in the AI field while working with cutting-edge technologies.
- Qualifications: Strong background in data science and proficiency in Python and SQL required.
- Other info: Ideal for those looking to grow their career in a dynamic, innovative environment.
The predicted salary is between 13 - 16 £ per hour.
Commitment: Part‑time, project‑based (15–25 hours/week, flexible up to 40 hours)
Role Responsibilities
- Review and refine AI‑generated prompts, responses, and code
- Validate technical concepts for accuracy and correctness
- Provide structured feedback on solution quality, clarity, and approach
- Tag and organize content by topic and difficulty level
- Support benchmarking efforts to assess AI model capabilities
Requirements
- Strong experience in data science, machine learning, or applied statistics
- Degree in Data Science, Statistics, Computer Science, Applied Mathematics, or a related field (Bachelor’s minimum; advanced degree preferred)
- Strong proficiency in Python and SQL; familiarity with R, Java, or Scala is a plus
- Hands‑on experience building and deploying ML models using frameworks such as scikit‑learn, TensorFlow, or PyTorch
- Experience with statistical analysis, data wrangling, and feature engineering on large datasets
Data Analyst | Remote in London employer: Crossing Hurdles
Contact Detail:
Crossing Hurdles Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst | Remote in London
✨Tip Number 1
Network like a pro! Reach out to folks in the data science community on LinkedIn or join relevant groups. 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 projects, especially those involving Python and SQL. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data analysis questions and coding challenges. Practise explaining your thought process clearly, as communication is key in this field.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Data Analyst | Remote in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science and machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing your Python and SQL prowess!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re passionate about data analysis and how your background makes you a perfect fit for our team. Keep it engaging and relevant to the job description.
Showcase Your Projects: If you've worked on any cool projects or have hands-on experience with ML models, make sure to mention them! We love seeing practical applications of your skills, especially if they involve frameworks like TensorFlow or PyTorch.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Crossing Hurdles
✨Know Your Data Inside Out
Make sure you brush up on your data science concepts, especially around machine learning and statistics. Be ready to discuss your past projects and how you've applied Python and SQL in real-world scenarios. This will show that you not only understand the theory but can also implement it effectively.
✨Prepare for Technical Questions
Expect technical questions related to AI-generated prompts and model validation. Practise explaining your thought process when reviewing code or providing feedback. You might even want to do a mock interview with a friend to get comfortable with articulating your ideas clearly.
✨Showcase Your Problem-Solving Skills
During the interview, be prepared to tackle hypothetical scenarios or case studies. Think about how you would approach tagging content or benchmarking AI models. Demonstrating your analytical thinking and structured approach will impress the interviewers.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects or challenges they face with AI models. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
