Part-Time AI Research Associate — MacBook Pro Required

Part-Time AI Research Associate — MacBook Pro Required

Part-Time 11.7 - 14.3 £ / hour (est.) Home office (partial)
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At a Glance

  • Tasks: Support AI research by developing questions and evaluation materials for advanced models.
  • Company: Join Mercor, a leading player in AI research with a focus on innovation.
  • Benefits: Flexible part-time hours, hands-on experience, and the chance to work with top AI experts.
  • Other info: Immediate start available; perfect for students looking to gain valuable experience.
  • Why this job: Be at the forefront of AI development and contribute to groundbreaking research.
  • Qualifications: Detail-oriented individuals with a passion for AI and research skills.

The predicted salary is between 11.7 - 14.3 £ per hour.

Mercor is seeking detail-oriented individuals to support a research project with a leading AI lab.

You will help benchmark and improve cutting-edge AI models as part of a small, focused team.

Part-time commitment of approximately 10-20 hours per week, with responsibilities including developing high-quality research questions, answers, and evaluation materials to train advanced language models.

Immediate start preferred.

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Part-Time AI Research Associate — MacBook Pro Required employer: Obsidian

Mercor is an excellent employer for those passionate about AI research, offering a collaborative work culture that fosters innovation and creativity. With flexible part-time hours, employees can balance their commitments while contributing to groundbreaking projects in a supportive environment that prioritises professional growth and development. Located in a vibrant tech hub, Mercor provides unique networking opportunities and access to industry-leading resources, making it an ideal place for aspiring researchers.

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Contact Details:

Obsidian Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Part-Time AI Research Associate — MacBook Pro Required

Get Involved in Data Challenges

Participate in data challenges like Kaggle competitions or DrivenData to showcase your skills and network with other data enthusiasts. Not only will you build your portfolio, but you can also catch the eye of potential employers like Obsidian.

Connect with Local Data Communities

Join local data science meetups or online communities like Data Science Society to engage with professionals in the field. These platforms are great for networking, discovering job opportunities, and keeping your fingers on the pulse of industry trends.

Leverage Your University’s Resources

If you're still in university, make full use of your career services. They might have part-time roles tailored for students like you, and often have direct connections with companies looking to hire talented interns in data science roles.

Apply Directly Through Our Website

Don’t forget to check out our jobs at Obsidian and apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate individuals like us who are eager to make an impact in the data science world.

We think you need these skills to ace Part-Time AI Research Associate — MacBook Pro Required

Attention to Detail
Research Skills
Benchmarking
AI Model Evaluation
Question Development
Language Model Training
Team Collaboration

Some tips for your application 🫡

Show Your Data Skills:In your CV, make sure to highlight your proficiency with key data analysis tools and programming languages like Python, R, or SQL. We want to see that you've got hands-on experience with data manipulation and visualisation, so if you've worked on any relevant projects or coursework, include those details to really showcase your skills!

Tailor Your Projects Towards Data Science:When it comes to your portfolio, focus on showcasing projects that highlight your data-science abilities. Include analyses, dashboards, or any predictive models you've built. If you've contributed to Kaggle competitions or have a GitHub repository with data projects, make sure to link those—these demonstrate your practical experience and problem-solving abilities.

Express Your Motivation in the Cover Letter:Since this is a part-time role, we want to know why you're particularly interested in juggling this with your other commitments. Use your cover letter to express your passion for data science and how this role at Obsidian aligns with your career aspirations. Show us you're excited about learning and growing with us!

Keep It Concise Yet Informative:Part-time positions often receive many applications, so keep your documents clear and to the point! Aim for a concise CV detailing your relevant experiences without unnecessary fluff. Be sure to include your availability in your cover letter as well—that helps us in the decision-making process!

How to prepare for a job interview at Obsidian

Brush Up on Your Stats!

Given you're eyeing a part-time role in data science, make sure you’re on top of your statistical methods and data analysis techniques. Expect questions around regression, hypothesis testing, and maybe even some statistical programming languages like R or Python during the interview with Obsidian.

Show Off Your Projects!

It's crucial to have a portfolio that showcases your data science projects. Highlight your part-time work with specific data sets, models you've built, or analyses you've conducted. Having tangible examples will demonstrate your hands-on experience and problem-solving skills to Obsidian.

Familiarise Yourself with Tools of the Trade

Make sure you’re well-versed in data science tools like Jupyter Notebook, Tableau, or SQL. You might get technical questions or even a practical test at Obsidian, so having a comfort level with these tools will definitely be an advantage.

Be Ready to Discuss Real-World Applications

Since this is a part-time role, employers at Obsidian will likely appreciate your understanding of how data science can address actual business problems. Be prepared to discuss any relevant case studies or how you would approach specific challenges in real scenarios.