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For Companies At a Glance
- Tasks: Design and implement graph solutions while collaborating with diverse teams.
- Company: Specialised analytics firm in Bristol with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Make a real impact by transforming data into accessible Knowledge Graphs.
- Qualifications: 3+ years in data science, strong Neo4j and Python skills required.
- Other info: Join a dynamic team and enhance your career in a thriving environment.
The predicted salary is between 36000 - 60000 £ per year.
A specialized analytics firm in Bristol seeks a Data Scientist focused on graph databases and ontology management. This role involves designing production-grade graph solutions, collaborating cross-functionally, and integrating diverse data into accessible Knowledge Graphs.
Ideal candidates will have at least 3 years in data science, strong Neo4j and Python skills, and experience deploying reliable systems. A master's degree in a related field is preferred.
Join us to impact operations, HR, and more through effective data modeling.
Graph Data Scientist: Knowledge Graphs & Production in Bristol employer: GM Analytic Software
Contact Detail:
GM Analytic Software Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graph Data Scientist: Knowledge Graphs & Production in Bristol
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your graph database projects, especially with Neo4j and Python. 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 knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to collaborate cross-functionally in this role.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Graph Data Scientist: Knowledge Graphs & Production in Bristol
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Neo4j and Python in your application. We want to see how you've used these skills in real-world projects, so don’t hold back!
Tailor Your Application: Take a moment to customise your CV and cover letter for this role. Mention specific projects or experiences that relate to graph databases and ontology management. It helps us see why you’re the perfect fit!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it’s relevant. Make it easy for us to understand your journey and achievements.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!
How to prepare for a job interview at GM Analytic Software
✨Know Your Graph Databases
Make sure you brush up on your knowledge of graph databases, especially Neo4j. Be prepared to discuss your previous projects and how you've used these technologies to solve real-world problems.
✨Showcase Your Python Skills
Since Python is a key requirement for this role, be ready to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice common data manipulation tasks and be familiar with libraries like Pandas and NetworkX.
✨Understand Ontology Management
Familiarise yourself with ontology management concepts. Be prepared to explain how you would approach designing a Knowledge Graph and integrating diverse data sources. This shows your ability to think critically about data structuring.
✨Collaborate and Communicate
This role involves cross-functional collaboration, so highlight your teamwork experiences. Share examples of how you've worked with different departments to achieve a common goal, as effective communication is key in this position.
