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For Companies At a Glance
- Tasks: Design advanced data science challenges and create rigorous technical solutions.
- Company: Alignerr, partnering with top AI research teams to innovate in AI models.
- Benefits: Competitive hourly pay, remote work flexibility, and opportunities for contract renewals.
- Why this job: Engage directly with industry-leading AI models and make a real impact.
- Qualifications: Master’s or PhD in Data Science or related field, strong analytical writing skills.
- Other info: Dynamic role with high agency and international reach.
The predicted salary is between 30 - 60 £ 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.
Organization 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 in Cambridge employer: Alignerr
Contact Detail:
Alignerr Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Expert - AI Content Specialist in Cambridge
✨Tip Number 1
Get your networking game on! Connect with professionals in the data science field on platforms like LinkedIn. Join relevant groups and participate in discussions to showcase your expertise and make valuable connections.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills. Practice explaining complex concepts like hyperparameter optimization or Bayesian inference in simple terms. This will help you communicate effectively during interviews and demonstrate your analytical writing skills.
✨Tip Number 3
Showcase your work! Create a portfolio of your projects, including any Python/R scripts or SQL queries you've developed. This not only highlights your technical abilities but also gives potential employers a glimpse into your problem-solving process.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining our team at Alignerr and contributing to cutting-edge AI research.
We think you need these skills to ace Data Science Expert - AI Content Specialist in Cambridge
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 details. Typos or formatting errors can distract from your qualifications. We appreciate precision, especially when it comes to code syntax and statistical conclusions!
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the quickest way for us to get your details and start the review process. Plus, we check applications daily, so don’t wait too long!
How to prepare for a job interview at Alignerr
✨Know Your Stuff
Make sure you brush up on advanced data science concepts like hyperparameter optimization 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.
✨Prepare for Technical Questions
Expect to face technical questions that challenge your understanding of AI models and data engineering pipelines. Practice explaining complex topics clearly and concisely, as you'll need to demonstrate your analytical writing skills during the interview. Use examples from your past work to illustrate your points.
✨Showcase Your Attention to Detail
Since this role requires a high level of precision, be prepared to discuss how you ensure accuracy in your work. Bring examples of how you've checked code syntax or validated statistical conclusions in previous projects. This will highlight your meticulous nature and commitment to quality.
✨Engage with the Interviewers
Don't hesitate to ask questions about the company's AI projects and their approach to model reasoning. Engaging with the interviewers shows your genuine interest in the role and helps you assess if it's the right fit for you. Plus, it gives you a chance to showcase your knowledge and enthusiasm for the field.
