Graph Data Analyst & Ontology Modeler (Remote) in London

Graph Data Analyst & Ontology Modeler (Remote) in London

London Full-Time 35000 - 45000 £ / year (est.) Working from home possible
Primus Connect

At a Glance

  • Tasks: Analyse and adapt veterinary data for the UK market using Neo4j.
  • Company: Join a leading pet insurance and veterinary services organisation.
  • Benefits: Remote work, competitive salary, and impactful data initiatives.
  • Other info: Collaborative environment with opportunities for professional growth.
  • Why this job: Make a difference in pet healthcare through innovative data analysis.
  • Qualifications: Experience with Neo4j, strong SQL skills, and effective communication.

The predicted salary is between 35000 - 45000 £ per year.

Primus Connect is looking for a skilled Data Analyst / Modeler to join a leading pet insurance and veterinary services organization. This remote role involves analyzing and adapting a US veterinary ontology for the UK market.

The ideal candidate will have:

  • Experience with Neo4j and data modelling
  • Strong SQL skills
  • The ability to communicate effectively between technical and clinical teams

This position offers the opportunity to work on impactful data initiatives.

Graph Data Analyst & Ontology Modeler (Remote) in London employer: Primus Connect

At Primus Connect, we pride ourselves on fostering a collaborative and innovative work culture that empowers our employees to make a real difference in the pet insurance and veterinary services sector. As a remote employer, we offer flexible working arrangements, competitive benefits, and ample opportunities for professional growth, ensuring that our team members can thrive while contributing to meaningful data initiatives that enhance animal care in the UK market.

Primus Connect

Contact Details:

Primus Connect Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Graph Data Analyst & Ontology Modeler (Remote) in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Primus Connect!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Graph Data Analyst & Ontology Modeler (Remote) at Primus Connect.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Primus Connect.

Apply Directly through Our Website

When you find a suitable opening like Graph Data Analyst & Ontology Modeler (Remote) at Primus Connect, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Graph Data Analyst & Ontology Modeler (Remote) in London

Data Analysis
Ontology Modelling
Neo4j
SQL
Communication Skills
Technical Team Collaboration
Clinical Team Collaboration

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Primus Connect, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Primus Connect. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Primus Connect

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Primus Connect!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.