At a Glance
- Tasks: Evaluate and improve AI-generated responses in data science using your expertise.
- Company: Join a cutting-edge AI project with a focus on innovation and independence.
- Benefits: Enjoy flexible remote work, competitive pay, and no shift or weekend commitments.
- Other info: Perfect for those seeking a dynamic role with growth opportunities in AI.
- Why this job: Make a real impact on the future of AI while working on exciting projects.
- Qualifications: Extensive Data Science experience and proficiency in Python or SQL required.
The predicted salary is between 31500 - 38500 £ per year.
About the Company
We are seeking experienced Data Science professionals to join a cutting-edge AI evaluation project as an AI Coder / AI Response Evaluator.
This is a unique opportunity to contribute to the development of next-generation Artificial Intelligence systems by applying your professional expertise to assess, validate, and improve AI-generated responses within your area of specialization.
This assignment is entirely remote, with flexible and self-directed working hours.
There is no patient care, no shift work, and no requirement to be available at specific times during the day.
Successful candidates will work independently while contributing to the training and improvement of advanced AI models.
About the Role
We are seeking experienced Data Science professionals to join a cutting-edge AI evaluation project as an AI Coder / AI Response Evaluator.
Responsibilities
- Review, assess, and evaluate AI-generated responses within data science and related technical domains.
- Analyze the accuracy, quality, completeness, and relevance of AI-produced outputs.
- Compare multiple AI-generated solutions and identify the strongest response based on technical merit.
- Evaluate Python, SQL, analytics, machine learning, statistical, and data engineering-related content.
- Provide clear written feedback and justification for evaluation decisions.
- Identify factual inaccuracies, logical errors, coding issues, and opportunities for improvement.
- Apply professional expertise to ensure responses align with real-world industry standards and best practices.
- Work independently while maintaining quality and productivity expectations.
- Participate in onboarding and qualification activities, including an initial paid assessment.
Qualifications
- Extensive Data Science experience in analytics, machine learning, statistical modeling, data engineering, business intelligence, artificial intelligence, or related applied disciplines.
- Undergraduate study does not count toward the minimum experience requirement.
- Working proficiency in Python and/or SQL, with the ability to read, understand, and evaluate technical code.
- Availability to commit 30-40 hours per week throughout the full 12-week assignment.
- Strong written communication skills and attention to detail.
- Ability to work independently in a fully remote environment.
- General familiarity with AI, Large Language Models (LLMs), or generative AI tools at a user level.
- Preferred Skills
- Advanced degree (Master's or Ph D) in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, Physics, or another quantitative discipline.
- Experience reviewing technical work, conducting quality assessments, or evaluating analytical outputs.
- Professional experience across multiple data domains, including machine learning, predictive analytics, experimentation, statistical inference, or data engineering.
- Exposure to generative AI technologies and AI-assisted coding tools.
- Pay range and compensation package
Successful candidates will be onboarded to the project and compensated for all approved hours worked throughout the assignment.
Equal Opportunity Statement
To ensure full transparency, this assignment does not involve patient care or clinical responsibilities, does not require shift work, on-call coverage, or weekend commitments, does not involve sales, business development, or customer support activities, and is not a traditional software engineering role focused on product development.
It focuses exclusively on evaluating and improving AI-generated content and technical outputs.
AI Trainer - Data Science in Hull employer: Planet Pharma
Join a leading biopharmaceutical organisation in Slough, where innovation meets collaboration. As a Scientist in Antibody Formulation Development, you'll thrive in a dynamic work culture that prioritises employee growth and offers unique opportunities to contribute to groundbreaking research. With a focus on professional development and a supportive team environment, this role promises a rewarding experience for those passionate about advancing biopharma solutions.
StudySmarter Expert Advice🤫
We think this is how you could land AI Trainer - Data Science in Hull
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Planet Pharma!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI Trainer - Data Science at Planet Pharma.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Planet Pharma.
✨Apply Directly through Our Website
When you find a suitable opening like AI Trainer - Data Science at Planet Pharma, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace AI Trainer - Data Science in Hull
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Planet Pharma, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Planet Pharma. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Planet Pharma
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Planet Pharma!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
