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- Tasks: Design advanced data science challenges and evaluate AI-generated code for accuracy.
- Company: Join Alignerr, a leader in AI research partnerships.
- Benefits: Competitive pay, remote work flexibility, and opportunities for contract renewals.
- Why this job: Work with cutting-edge AI models and make a real impact in the tech industry.
- Qualifications: Master's or PhD in Data Science or related field; strong analytical skills required.
- Other info: Dynamic role with high agency and international reach.
The predicted salary is between 26 - 52 ÂŁ per hour.
This role is part of Alignerr’s partnership with leading AI research teams and labs to build and train cutting‑edge AI models.
Base Pay Range: $40.00/hr - $80.00/hr
Location: Remote
Commitment: 10–40 hours/week
Type: Hourly Contract
What You’ll Do:
- Design advanced data science challenges across domains such as hyperparameter optimization, Bayesian inference, cross‑validation strategies, and dimensionality reduction.
- Create rigorous, step‑by‑step technical solutions—including Python/R scripts, SQL queries, and mathematical derivations—that serve as “golden responses.”
- Evaluate AI‑generated code, data visualizations, and statistical summaries for technical accuracy and efficiency using tools like Scikit‑Learn, PyTorch, or TensorFlow.
- Identify logical fallacies in AI reasoning—e.g., data leakage, overfitting, improper handling of imbalanced datasets—and provide structured feedback to improve the model’s reasoning process.
Requirements:
- Advanced degree: Master’s (pursuing or completed) or PhD in Data Science, Statistics, Computer Science, or a related quantitative field.
- Strong foundational knowledge in supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP.
- Excellent analytical writing skills to communicate highly technical algorithmic concepts and statistical results clearly and concisely.
- High level of precision when checking code syntax, mathematical notation, and the validity of statistical conclusions.
- No prior 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, international reach.
- 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.
About the role:
- Seniority level: Internship
- Employment type: Contract
- Job function: Engineering and Information Technology
- Industry: Technology, Information and Internet
Data Scientist (Masters) - AI Data Trainer in Christchurch employer: Alignerr
Contact Detail:
Alignerr Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Masters) - AI Data Trainer in Christchurch
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, join relevant online communities, and attend virtual meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, R, or any AI models you've worked on. 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 practising common data science problems. Use platforms like StudySmarter to review key topics and get comfortable explaining your thought process during coding challenges.
✨Tip Number 4
Apply through our website! It’s quick and easy, plus our team reviews applications daily. Make sure to complete your AI interview and application steps to boost your chances of landing that Data Scientist role.
We think you need these skills to ace Data Scientist (Masters) - AI Data Trainer in Christchurch
Some tips for your application 🫡
Tailor Your Resume: Make sure your resume highlights the skills and experiences that align with the Data Scientist role. Use keywords from the job description to show us you’re a perfect fit!
Show Off Your Analytical Writing Skills: Since we value clear communication of complex ideas, include examples in your application that demonstrate your ability to explain technical concepts concisely. This will help us see your analytical writing prowess!
Be Precise and Detail-Oriented: When filling out your application, pay close attention to detail. We love candidates who double-check their work, so make sure there are no typos or errors in your submission.
Apply Through Our Website: To ensure your application gets the attention it deserves, apply directly through our website. It’s quick and easy, and we review applications daily, so don’t miss out!
How to prepare for a job interview at Alignerr
✨Know Your Data Science Fundamentals
Brush up on your knowledge of supervised and unsupervised learning, as well as deep learning concepts. Be ready to discuss how you would approach challenges like hyperparameter optimization or dimensionality reduction, as these are key aspects of the role.
✨Showcase Your Technical Skills
Prepare to demonstrate your proficiency in Python, R, SQL, and tools like Scikit-Learn or TensorFlow. Bring examples of your previous work or projects that highlight your ability to create rigorous technical solutions and evaluate AI-generated outputs.
✨Communicate Clearly and Concisely
Since excellent analytical writing skills are a must, practice explaining complex algorithmic concepts in simple terms. You might be asked to present your thought process during the interview, so clarity is key!
✨Be Ready for Problem-Solving Questions
Expect to tackle some real-world data science problems during the interview. Think about how you would identify logical fallacies in AI reasoning or handle imbalanced datasets, and be prepared to provide structured feedback on these issues.
