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- Tasks: Join a team to evaluate and improve generative AI models through innovative data analysis.
- Company: Dynamic tech company focused on cutting-edge AI solutions.
- Benefits: Healthcare contributions, pension scheme, work laptop, 25 days leave, and career progression.
- Why this job: Make a real impact in the exciting field of generative AI and enhance user experiences.
- Qualifications: Basic knowledge of Python, SQL, and computer vision; strong communication and problem-solving skills.
- Other info: Hybrid work model with opportunities for growth in a rapidly evolving industry.
The predicted salary is between 36000 - 60000 £ per year.
Our client is seeking a Data Analyst for 12 months and will be Hybrid (3 days in office per week). Despite rapid development in generative AI, quality measurement remains challenging due to the lack of reliable and robust technical metrics. This is especially the case when the slight differences in the details generated by the model could have a significant impact on user experience. In this team, we are developing a series of manual (human rating), semi-automatic, and fully automatic evaluations to measure the quality of our image and video generative models (text to image, image to video, text to video, etc.) in a variety of quality axes, including visual quality, prompt following, identity preservation, naturalness, and visual text generation.
Responsibilities
- Working with the team to prototype human rating and semi-automatic model evaluation protocols.
- For high stake and/or high complexity protocols, conduct small-to-medium scale in-house human rating on generated content.
- Working with engineers to identify and summarise model gaps based on the above evaluation.
- Working with engineers to identify data needed to close those gaps and mine such data to prepare training data for the next iteration of model training.
- Working with PDO teams to scale up validated evaluation protocols, including coordination and auditing.
Qualifications
- Verbal and written communication skills, problem solving skills, and interpersonal skills.
- Attention to details and an aptitude for experimental investigations.
- Basic ability to work independently and manage one’s time.
- Basic knowledge of Python, Unix, and SQL.
- Basic knowledge of computer vision and generative models.
- Associate's degree or equivalent training required in Computer Science, Electronic Engineering, Physics, Bioinformatics, or other STEM subjects.
- Prior industrial experience in software development and testing and/or research experience in human-computer interaction are preferred.
Benefits
- Healthcare contribution and inclusion in company pension scheme.
- Work laptop and phone.
- 25 days annual leave (pro-rata) plus paid bank holidays.
- Expanding workforce with potential for career progression for top performers.
Data Analyst employer: Mackin Talent
Contact Detail:
Mackin Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by practising common data analyst questions. Get comfortable with explaining your thought process and showcasing your problem-solving skills. We recommend doing mock interviews with friends or using online platforms.
✨Tip Number 3
Show off your skills! Create a portfolio of projects that highlight your experience with Python, SQL, and any relevant data analysis work. This will give you an edge and demonstrate your capabilities to potential employers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Analyst role. Highlight relevant skills like Python, SQL, and any experience with generative models. We want to see how your background fits with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data analysis and how you can contribute to our team. Keep it concise but engaging – we love a good story!
Showcase Your Attention to Detail: Since attention to detail is key for this role, make sure your application is free from typos and errors. We appreciate candidates who take the time to present their work neatly and professionally.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it’s super easy!
How to prepare for a job interview at Mackin Talent
✨Know Your Data
Make sure you brush up on your data analysis skills, especially in Python, SQL, and any relevant tools. Be prepared to discuss how you've used these skills in past projects or roles, as this will show your practical experience and understanding of the technical requirements.
✨Understand the Role
Familiarise yourself with the specifics of the job description. Understand the importance of quality measurement in generative AI and be ready to discuss how you can contribute to developing evaluation protocols. This shows that you’re not just interested in the role, but also in the company’s mission.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities. Think of examples from your past experiences where you identified gaps in data or processes and how you addressed them. This will demonstrate your analytical thinking and ability to work independently.
✨Show Your Communication Skills
Since the role requires collaboration with engineers and other teams, be ready to showcase your verbal and written communication skills. Practice explaining complex concepts in simple terms, as this will highlight your ability to work well with others and convey your ideas effectively.
