At a Glance
- Tasks: Label and annotate diverse data types for machine learning projects.
- Company: Atreides is a startup transforming data into geo-spatial insights for defense intelligence.
- Benefits: Enjoy competitive salary, stock options, flexible hours, and generous vacation.
- Why this job: Join an innovative team making the world safer while developing your data science skills.
- Qualifications: Attention to detail and basic understanding of data science principles required.
- Other info: Remote work with one day onsite; active SC clearance needed.
The predicted salary is between 24000 - 36000 £ per year.
Position: Data Labeler Location: West Midlands region U.K. (remote with 1 day per week onsite) Clearance: Active SC clearance (UK MOD clearance Company Overview: Atreides is a cutting-edge startup transforming complex data into actionable geo-spatial insights for defense intelligence professionals. Backed by a top venture firm, we’re on a mission to make the world safer and more resilient. Join our high-performance team and be part of something innovative! What We’re Looking For: We are looking for a meticulous and motivated Data Labeler to join our Data Science team. In this role, you will be responsible for accurately labeling and annotating datasets to support various data science projects, including machine learning model development and data analysis. Your contributions will be critical in ensuring the quality and reliability of data used for training and validating models. Key Responsibilities: • Label and annotate diverse types of data, including text, images, audio, and video, in accordance with project specifications and guidelines. • Ensure high levels of accuracy and consistency in labeling to maintain the integrity of datasets. • Collaborate closely with data scientists and analysts to understand specific data requirements and objectives. • Use data labeling tools and software efficiently to streamline the annotation process. • Conduct quality checks on labeled data, identifying and correcting any discrepancies or errors. • Maintain detailed records of labeling processes and adhere to project timelines. • Participate in training and feedback sessions to enhance labeling guidelines and improve overall data quality. Qualifications: • Strong attention to detail and a commitment to producing high-quality work. • Familiarity with data labeling tools is a plus, but not required. • Basic understanding of data science principles and the importance of labeled data in model training. • Ability to work both independently and collaboratively within a team environment. Skills: • Proficient in using common software applications and tools for data annotation. • Strong communication skills to facilitate effective collaboration with team members. • Problem-solving abilities to address challenges during the labeling process. • Basic technical skills to understand data formats and structures. Why Atreides? • Competitive Salary + Stock Option and Comprehensive Health Benefits • Flexible Hybrid Work Environment + Flexible Hours • Work Travel Opportunities + Generous Vacation Excited to drive the future of defense intelligence? If you’re passionate, innovative, and ready for a challenge, we’d love to hear from you!
Data Labeler employer: Atreides
Contact Detail:
Atreides Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Labeler
✨Tip Number 1
Familiarize yourself with common data labeling tools and software. Even if you don't have prior experience, showing a willingness to learn these tools can set you apart from other candidates.
✨Tip Number 2
Highlight any experience you have with data analysis or machine learning principles. Understanding the importance of labeled data in model training will demonstrate your commitment to the role.
✨Tip Number 3
Prepare to discuss your attention to detail and problem-solving skills during the interview. Be ready to provide examples of how you've maintained accuracy in previous tasks or projects.
✨Tip Number 4
Emphasize your ability to work both independently and as part of a team. Atreides values collaboration, so showcasing your teamwork skills will be beneficial.
We think you need these skills to ace Data Labeler
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Data Labeler. Familiarize yourself with data labeling processes and the importance of accuracy in this role.
Tailor Your CV: Customize your CV to highlight relevant experience and skills that align with the job description. Emphasize your attention to detail, any familiarity with data labeling tools, and your ability to work both independently and as part of a team.
Craft a Strong Cover Letter: Write a compelling cover letter that showcases your passion for data science and your motivation to contribute to Atreides' mission. Mention specific examples of how your skills and experiences make you a great fit for the Data Labeler position.
Proofread Your Application: Before submitting, carefully proofread your application materials. Check for any spelling or grammatical errors, and ensure that all information is clear and concise. A polished application reflects your commitment to quality.
How to prepare for a job interview at Atreides
✨Show Your Attention to Detail
As a Data Labeler, attention to detail is crucial. Be prepared to discuss examples from your past experiences where your meticulous nature led to high-quality outcomes. Highlight any specific projects where accuracy was key.
✨Familiarize Yourself with Data Labeling Tools
Even if you haven't used data labeling tools before, showing a willingness to learn can set you apart. Research common tools used in the industry and be ready to discuss how you would approach learning new software quickly.
✨Understand the Importance of Labeled Data
Demonstrate your understanding of how labeled data impacts machine learning models. Be ready to explain why accurate labeling is essential for model training and validation, and how it contributes to the overall success of data science projects.
✨Prepare for Collaboration Questions
Since collaboration is key in this role, think of examples where you've worked effectively within a team. Be ready to discuss how you communicate with team members and resolve conflicts, especially in a remote work environment.