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- Tasks: Conduct experiments and manage knowledge graph development while integrating ML techniques.
- Company: Leading technology company in London with a focus on innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Join a team that applies cutting-edge ML techniques to real-world data.
- Qualifications: PhD or Master's degree with industry experience in NLP and graph-based ML.
- Other info: Dynamic environment fostering collaboration and creativity.
The predicted salary is between 43200 - 72000 £ per year.
A leading technology company in London is seeking a Senior Applied Scientist specializing in Knowledge Graphs and Machine Learning. You will conduct experiments, manage knowledge graph development, and collaborate with teams to integrate ML techniques in applications.
The ideal candidate will have a PhD or Master's degree, industry experience, and strong expertise in NLP and graph-based ML applications. This role emphasizes innovation and real-world data application within a hybrid work model.
Senior Knowledge Graphs in England employer: Refinitiv
Contact Detail:
Refinitiv Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Knowledge Graphs in England
✨Tip Number 1
Network like a pro! Reach out to professionals in the Knowledge Graphs and Machine Learning space on LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Showcase your expertise! Create a portfolio or GitHub repository with projects that highlight your skills in NLP and graph-based ML applications. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common interview questions related to Knowledge Graphs and Machine Learning to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We often have exclusive job listings that might not be found elsewhere, so keep an eye out for opportunities that match your skills and interests.
We think you need these skills to ace Senior Knowledge Graphs in England
Some tips for your application 🫡
Show Off Your Expertise: Make sure to highlight your experience with Knowledge Graphs and Machine Learning in your application. We want to see how your skills align with the role, so don’t hold back on showcasing your PhD or Master’s degree and any relevant industry experience.
Tailor Your Application: Take a moment to customise your CV and cover letter for this specific role. We love seeing candidates who understand our needs and can demonstrate how their background in NLP and graph-based ML applications fits perfectly with what we’re looking for.
Be Innovative: Since this role emphasises innovation, don’t shy away from sharing your creative ideas or past projects that showcase your ability to apply real-world data in novel ways. We’re all about fresh perspectives here at StudySmarter!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Refinitiv
✨Know Your Graphs
Make sure you brush up on your knowledge of Knowledge Graphs and their applications. Be ready to discuss specific projects you've worked on, especially those involving NLP and machine learning. This will show your expertise and how you can contribute to the company's goals.
✨Showcase Your Experiments
Prepare to talk about the experiments you've conducted in your previous roles. Highlight the methodologies you used, the challenges you faced, and the outcomes. This demonstrates your hands-on experience and problem-solving skills, which are crucial for this position.
✨Collaboration is Key
Since the role involves working with various teams, be ready to discuss your experience in collaborative projects. Share examples of how you’ve successfully integrated ML techniques into applications and how you’ve communicated complex ideas to non-technical stakeholders.
✨Embrace Innovation
This company values innovation, so come prepared with ideas on how to apply real-world data to improve knowledge graph development. Think about recent trends in the field and be ready to share your thoughts on future directions for knowledge graphs and machine learning.
