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- Tasks: Create and manage data labels while optimising the labelling process.
- Company: Join a forward-thinking team focused on AI and ML development.
- Benefits: Enjoy flexible working options and opportunities for professional growth.
- Why this job: Be part of a mission to uphold content integrity and authenticity.
- Qualifications: Bachelor's degree or equivalent experience in relevant fields required.
- Other info: Exposure to new technologies and collaboration with cross-functional teams.
The predicted salary is between 36000 - 60000 £ per year.
The main function of a Data Labeling Analyst is to create and manage data labels while collaborating closely with our operations team to generate insights and optimise the labeling process. You will play a pivotal role in the development of AI and ML models, ensuring the accuracy and relevance across both integrity and support use cases. A key aspect of the role will involve identifying and addressing instances of bad actors or misrepresentation within data sets to uphold the integrity and authenticity of the content. While this role is not expected to engage with graphic content, there is a risk of some exposure.
Responsibilities:
- Become an expert in various integrity and support issues across Operations.
- Create and modify data labels, ensuring compliance with all regulatory and legal requirements.
- Ensure the quality of labelled data sets, ensuring alignment with content policies and/or support processes.
- Partner with team members to improve processes and tools of the team's labelling interfaces.
- Deliver insights as appropriate related to observed trends in data labelling workflows.
- Identify, investigate, and flag instances of bad actors or misrepresentation within data sets, ensuring compliance with standards for integrity and authenticity.
- Collaborate with cross-functional teams (XFNs) to develop strategies for detecting and mitigating bad actor activity or content misrepresentation.
Typical Day in the Role:
- Policy reasoning rationing
- Conducting review/investigation work for a specific tool - annotating on content
- Set number of annotations to be confirmed
- Working with (tech, integrity and product)
- New technology, skills set critical thinking and strong language skills, articulate to Gen AI why its good and/or bad, language is key, have to be able to communicate effectively.
- Can collaborate with stakeholders, take insights and translate to technical teams.
Required Qualifications:
- Bachelor's degree or equivalent work experience in related field(s) (e.g. Computer Science, Information Systems, Intelligence Studies, Cybersecurity, Mathematics, Business Administration, etc.).
- Professional experience in an office setting, working in an autonomous role.
- Experience in data review and/or labelling processes.
- Ability to identify trends within large data sets.
Escalation Specialist employer: Morgan McKinley
Contact Detail:
Morgan McKinley Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Escalation Specialist
✨Tip Number 1
Familiarise yourself with the latest trends in AI and machine learning, especially in data labelling. Understanding how these technologies work will help you demonstrate your expertise during interviews.
✨Tip Number 2
Network with professionals in the field of data integrity and safety. Join relevant online forums or LinkedIn groups to connect with others who can provide insights or even refer you to opportunities at StudySmarter.
✨Tip Number 3
Prepare to discuss specific examples of how you've identified trends in data sets or improved processes in previous roles. This will showcase your analytical skills and problem-solving abilities, which are crucial for the Escalation Specialist position.
✨Tip Number 4
Stay updated on compliance regulations related to data labelling and integrity. Being knowledgeable about legal requirements will not only help you in the role but also impress us during the interview process.
We think you need these skills to ace Escalation Specialist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data labelling, analysis, and any related fields. Emphasise your skills in identifying trends within large data sets and your ability to work autonomously.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role of Escalation Specialist. Discuss how your background aligns with the responsibilities outlined in the job description, particularly your experience with data integrity and collaboration with cross-functional teams.
Showcase Relevant Skills: Highlight specific skills that are crucial for this role, such as critical thinking, attention to detail, and strong language proficiency. Provide examples of how you've successfully applied these skills in previous roles.
Proofread Your Application: Before submitting your application, carefully proofread all documents for spelling and grammatical errors. A polished application reflects your attention to detail and professionalism, which are key for this position.
How to prepare for a job interview at Morgan McKinley
✨Understand the Role
Make sure you thoroughly understand the responsibilities of a Data Labelling Analyst. Familiarise yourself with data labelling processes, integrity issues, and how they relate to AI and ML models. This will help you answer questions confidently and demonstrate your knowledge.
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with data review and identifying trends within large data sets. Use specific examples from your past work to illustrate your analytical abilities and how they can benefit the team.
✨Communicate Effectively
Since the role requires collaboration with cross-functional teams, practice articulating your thoughts clearly. You might be asked to explain complex concepts, so being able to communicate effectively is crucial.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills, especially in identifying bad actors or misrepresentation in data sets. Think of scenarios where you had to make critical decisions and be ready to discuss your thought process.
