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For Companies At a Glance
- Tasks: Design advanced data science challenges and create rigorous technical solutions.
- Company: Alignerr, a leader in AI research collaboration.
- Benefits: Competitive hourly pay, remote work, and flexible hours.
- Why this job: Engage with cutting-edge AI models and make a real impact.
- Qualifications: Master’s or PhD in Data Science or related field required.
- Other info: Join a dynamic team with opportunities for growth and renewal.
The predicted salary is between 30 - 60 ÂŁ per hour.
About The Job
At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting-edge AI models. You’ll challenge advanced language models on topics like machine learning theory, statistical inference, neural network architectures, and data engineering pipelines—documenting every failure mode so we can harden model reasoning.
Position: Data Science Expert - AI Content Specialist
Type: Hourly Contract
Compensation: $40–$80 /hour
Location: Remote
Commitment: 10–40 hours/week
What You’ll Do
- Develop Complex Problems: Design advanced data science challenges across domains like hyperparameter optimization, Bayesian inference, cross-validation strategies, and dimensionality reduction.
- Author Ground-Truth Solutions: Create rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as "golden responses."
- Technical Auditing: Evaluate AI-generated code (using libraries like Scikit-Learn, PyTorch, or TensorFlow), data visualizations, and statistical summaries for technical accuracy and efficiency.
- Refine Reasoning: Identify logical fallacies in AI reasoning—such as data leakage, overfitting, or improper handling of imbalanced datasets—and provide structured feedback to improve the model's "thinking" process.
Requirements
- Advanced Degree: Master’s (pursuing or completed) or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a heavy emphasis on data analysis.
- Domain Expertise: Strong foundational knowledge in core areas such as supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP.
- Analytical Writing: The ability to communicate highly technical algorithmic concepts and statistical results clearly and concisely in written form.
- Attention to Detail: High level of precision when checking code syntax, mathematical notation, and the validity of statistical conclusions. No AI experience required.
Preferred
- Prior experience with data annotation, data quality, or evaluation systems.
- Proficiency in production-level data science workflows (e.g., MLOps, CI/CD for models).
Why Join Us
- Excellent compensation with location-independent flexibility.
- Direct engagement with industry-leading LLMs.
- Contractor advantages: high agency, agility, and international reach.
- More opportunities for contracting renewals.
Application Process (Takes 15-20 min)
- Submit your resume.
- Complete a short screening.
- Project matching and onboarding.
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Data Science Expert - AI Content Specialist employer: Alignerr
Contact Detail:
Alignerr Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Expert - AI Content Specialist
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field and let them know you're on the lookout for opportunities. A personal recommendation can go a long way in landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those related to AI and data science. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on technical concepts and common questions in data science. Practice explaining complex ideas clearly—this is key when discussing topics like machine learning or statistical inference.
✨Tip Number 4
Don't forget to apply through our website! It’s the quickest way to get noticed by our team. Plus, we review applications daily, so you won't be left waiting around for a response.
We think you need these skills to ace Data Science Expert - AI Content Specialist
Some tips for your application 🫡
Craft a Tailored Resume: Make sure your resume highlights your relevant experience in data science and AI. We want to see how your skills align with the job description, so don’t be shy about showcasing your expertise in machine learning and statistical inference!
Show Off Your Analytical Writing Skills: Since clear communication is key for this role, include examples of your technical writing. Whether it’s a blog post, a research paper, or documentation, we love seeing how you can break down complex concepts into digestible content.
Be Detail-Oriented: Pay close attention to your application materials. Typos or errors can distract from your qualifications. We appreciate precision, especially when it comes to code syntax and statistical conclusions, so double-check everything before hitting submit!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you’re considered promptly. Plus, it only takes 15-20 minutes—easy peasy!
How to prepare for a job interview at Alignerr
✨Know Your Stuff
Make sure you brush up on advanced data science concepts like hyperparameter optimisation and Bayesian inference. Be ready to discuss your experience with Python, R, and SQL, as well as any relevant projects you've worked on. This will show that you're not just familiar with the theory but can also apply it practically.
✨Showcase Your Analytical Writing
Since clear communication of complex ideas is key, prepare to demonstrate your analytical writing skills. Bring examples of your previous work where you've explained technical concepts or solutions. This could be a great way to highlight your ability to convey intricate information in an understandable manner.
✨Prepare for Technical Audits
Expect to evaluate AI-generated code during the interview. Familiarise yourself with libraries like Scikit-Learn, PyTorch, and TensorFlow. Practise auditing sample codes for accuracy and efficiency, as this will help you feel more confident when discussing your findings.
✨Attention to Detail is Key
Demonstrate your meticulous nature by preparing to discuss how you ensure precision in your work. Whether it's checking code syntax or validating statistical conclusions, be ready to share specific examples of how you've maintained high standards in your previous roles.
