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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-notch professionals in a dynamic environment.
- Qualifications: PhD or Master's in a relevant field, plus experience in Knowledge Graphs and ML.
- 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.
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 them, as this will demonstrate your expertise and relevance to the role.
✨Tip Number 2
Brush up on your NLP knowledge and be ready to discuss various state-of-the-art techniques. Familiarise yourself with recent advancements in the field, as being able to speak confidently about these can set you apart during interviews.
✨Tip Number 3
Practice explaining complex technical concepts in simple terms. Since you'll need to communicate with both technical and non-technical stakeholders, being able to convey your ideas clearly will be crucial for success in this role.
✨Tip Number 4
Engage with the data science community online, especially around topics like MLOps and ML experimentation. Networking with professionals in the field can provide insights and potentially lead to referrals, increasing your chances of landing the job.
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. Use specific examples 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 collaboration with stakeholders.
Showcase Relevant Projects: If you have worked on projects involving Knowledge Graphs or NLP, include them in your application. Describe your role, the technologies used, and the outcomes achieved to illustrate your capabilities.
Highlight Communication Skills: Since the role requires effective communication with both technical and non-technical stakeholders, emphasise any experience you have in this area. Provide examples of how you've successfully conveyed complex information in the past.
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 and modern ML frameworks like PyTorch or TensorFlow. Brush up on your coding skills and be ready to solve problems on the spot, as this will showcase your technical abilities and problem-solving mindset.
