Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build RAG and predictive models using Airtable data to drive insights.
- Company: Join a forward-thinking team focused on data-driven decision-making.
- Benefits: Flexible contract, remote work, and the chance to enhance your skills.
- Why this job: Make an impact with your data science skills in a dynamic environment.
- Qualifications: Experience in Python, R, machine learning, and data analysis required.
- Other info: Contract duration of 1 to 3 months, 30 hours per week.
The predicted salary is between 500 - 1500 £ per month.
We are looking for an experienced data scientist to assist in building a RAG (Retrieval Augmented Generation) and predictive model using our dataset from Airtable. This person is also able to design a way to train the model. The ideal candidate will have a strong understanding of model development processes, data cleaning, and predictive analytics. Your expertise will help us derive valuable insights and build robust models to enhance our decision-making capabilities. If you have a proven track record in predictive modeling and are comfortable working with Airtable data, we would love to hear from you.
Contract duration of 1 to 3 months with 30 hours per week.
Mandatory skills:- Python
- Data Science
- R
- Machine Learning
- Data Analysis
- Statistics
- Zapier
Data Scientist Needed for RAG + Predictive Model Development employer: FreelanceJobs
Contact Detail:
FreelanceJobs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist Needed for RAG + Predictive Model Development
✨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. You never know who might have a lead or can refer you to someone looking for a data scientist.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous projects, especially those involving predictive modelling and RAG. 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 your technical skills. Be ready to discuss your experience with Python, R, and machine learning. Practising common interview questions can help you feel more confident when it’s time to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented data scientists like you. Keep an eye on our job postings and make sure to submit your application directly for the best chance at landing that dream role.
We think you need these skills to ace Data Scientist Needed for RAG + Predictive Model Development
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, R, and predictive modelling. We want to see how your skills align with our needs, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re passionate about data science and how your expertise can help us build robust models. Keep it engaging and personal – we love a good story!
Showcase Your Projects: If you've worked on any cool projects involving RAG or predictive models, make sure to mention them! We’re keen to see your hands-on experience and how you’ve tackled challenges in the past.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at FreelanceJobs
✨Know Your Models
Make sure you brush up on your knowledge of predictive models and RAG. Be ready to discuss your previous experiences with model development, including any challenges you faced and how you overcame them.
✨Showcase Your Data Skills
Since the role involves working with Airtable data, be prepared to talk about your data cleaning techniques and how you've used Python and R in past projects. Bring examples of your work that highlight your data analysis skills.
✨Prepare for Technical Questions
Expect technical questions related to machine learning and statistics. We recommend reviewing key concepts and being ready to explain your thought process when developing models or analysing data.
✨Ask Insightful Questions
At the end of the interview, don’t hesitate to ask questions about the team’s current projects or the tools they use. This shows your genuine interest in the role and helps you understand how you can contribute effectively.
