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- Tasks: Join us as a Data Scientist to innovate with NLP and Knowledge Graphs.
- Company: Work with a cutting-edge tech company focused on risk and fraud solutions.
- Benefits: Enjoy a fully remote role with flexible hours and a collaborative culture.
- Why this job: Make an impact in AI while working with top-tier professionals in a dynamic environment.
- Qualifications: PhD or Master's in a relevant field, plus experience in Knowledge Graphs and Python.
- Other info: This is a contract role outside IR35 for an initial 9 months.
The predicted salary is between 48000 - 72000 £ per year.
I am currently immediately looking for a vastly talented Data Scientist with expert level Knowledge Graph experience to join my client on a fully remote contract. As a Data Scientist, you will be working on NLP applications for risk, fraud, and investigation products.
Your job will be to:
- Experiment with different state-of-the-art as well as traditional NLP approaches to find the best solution for the given problem.
- Work with all things Knowledge Graph related.
- Independently determine appropriate data and modelling choices.
- Effectively communicate with technical and non-technical stakeholders.
- Follow best practices for ML experimentation and MLOps.
Required Qualifications:
- PhD in a relevant discipline or Master’s plus a comparable level of experience.
- Experienced in Knowledge Graphs.
- Experience with traditional ML models and feature engineering.
- Experience with LLMs.
- Strong programming skills (e.g., Python) and experience with modern ML frameworks (e.g., PyTorch, TensorFlow, LangChain).
- Collaborating with other Researchers, Product, Engineering and Business Stakeholders in an agile manner to demonstrate value and iterate with customer feedback.
For immediate consideration, please apply today.
Data Scientist (Knowledge Graph) employer: Greybridge Search & Selection
Contact Detail:
Greybridge Search & Selection Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Knowledge Graph)
✨Tip Number 1
Make sure to showcase your experience with Knowledge Graphs in your conversations. Prepare specific examples of projects where you've successfully implemented Knowledge Graph techniques, as this will demonstrate your expertise and relevance for the role.
✨Tip Number 2
Brush up on your NLP knowledge and be ready to discuss various state-of-the-art approaches. Familiarise yourself with recent advancements in NLP and be prepared to share your thoughts on how they could apply to risk and fraud detection.
✨Tip Number 3
Since communication is key in this role, practice explaining complex technical concepts in simple terms. This will help you effectively engage with both technical and non-technical stakeholders during interviews.
✨Tip Number 4
Familiarise yourself with MLOps best practices, as this role involves following these principles. Be ready to discuss how you've applied MLOps in past projects, which will show your understanding of the entire machine learning lifecycle.
We think you need these skills to ace Data Scientist (Knowledge Graph)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Knowledge Graphs, NLP applications, and relevant programming skills like Python. Use specific examples from your past work to demonstrate your expertise in these areas.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about the role and how your background aligns with the company's needs. Mention your experience with ML experimentation and MLOps, as well as your ability to communicate effectively with both technical and non-technical stakeholders.
Showcase Relevant Projects: If you have worked on projects involving Knowledge Graphs or NLP, be sure to include them in your application. Describe your role, the challenges you faced, and the outcomes of your work to illustrate your capabilities.
Highlight Collaboration Skills: Since the role involves working with various stakeholders, emphasise your experience in collaborative environments. Provide examples of how you've successfully worked with researchers, product teams, and business stakeholders to achieve project goals.
How to prepare for a job interview at Greybridge Search & Selection
✨Showcase Your Knowledge Graph Expertise
Be prepared to discuss your experience with Knowledge Graphs in detail. Highlight specific projects where you've implemented them, the challenges you faced, and how you overcame them. This will demonstrate your depth of knowledge and practical skills.
✨Demonstrate NLP Proficiency
Since the role involves NLP applications, be ready to talk about various NLP techniques you've used. Discuss any state-of-the-art models or traditional approaches you've experimented with, and explain how you determined the best solution for specific problems.
✨Communicate Effectively
You'll need to interact with both technical and non-technical stakeholders. Practice explaining complex concepts in simple terms. This will show that you can bridge the gap between different teams and ensure everyone is on the same page.
✨Prepare for Technical Questions
Expect questions related to Python programming, ML frameworks like PyTorch or TensorFlow, and feature engineering. Brush up on these topics and be ready to solve coding problems or discuss your thought process during the interview.
