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- Tasks: Use data analysis and machine learning to drive business decisions and create visualisations.
- Company: Leading legal services provider in the UK with a focus on innovation.
- Benefits: 26 days holiday, flexible working options, and a generous benefits package.
- Why this job: Join a dynamic team and make impactful decisions using cutting-edge data techniques.
- Qualifications: Advanced skills in Python, R, SQL Server, and experience in advanced analytics.
- Other info: Opportunity to mentor junior members and grow your career in a supportive environment.
The predicted salary is between 36000 - 60000 £ per year.
A leading legal services provider in the UK seeks a Data Scientist to join their Information Management Team. In this role, you will leverage data analysis techniques and machine learning to guide business decisions.
Key responsibilities include:
- Creating data visualizations
- Mentoring junior team members
The ideal candidate will have advanced proficiency in Python, R, SQL Server, and experience in advanced analytics.
This position offers a generous benefits package including 26 days of holiday and flexible working options.
Data Scientist — AI, ML & Insurance Insights employer: ARAG Legal Services UK
Contact Detail:
ARAG Legal Services UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist — AI, ML & Insurance Insights
✨Tip Number 1
Network like a pro! Reach out to current employees in the company or industry on LinkedIn. A friendly chat can give us insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data visualisations and machine learning projects. This is a great way to demonstrate your advanced proficiency in Python, R, and SQL Server.
✨Tip Number 3
Prepare for the interview by brushing up on common data science questions and case studies. We should also be ready to discuss how we can mentor junior team members, as that’s a key part of the 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, it shows you’re genuinely interested in joining the team.
We think you need these skills to ace Data Scientist — AI, ML & Insurance Insights
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, R, and SQL Server. We want to see how your skills align with the role, so don’t be shy about showcasing your advanced analytics expertise!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data science and how you can contribute to our Information Management Team. Let us know what excites you about the role!
Showcase Your Projects: If you've worked on any relevant projects, make sure to mention them! Whether it's data visualisations or machine learning models, we love seeing real-world applications of your skills.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at ARAG Legal Services UK
✨Know Your Data Tools
Make sure you brush up on your skills in Python, R, and SQL Server. Be ready to discuss specific projects where you've used these tools, as well as any challenges you faced and how you overcame them.
✨Showcase Your Analytical Mindset
Prepare to talk about your approach to data analysis and machine learning. Think of examples where your insights led to significant business decisions, and be ready to explain your thought process clearly.
✨Visualisation is Key
Since creating data visualisations is part of the role, practice explaining your visualisation techniques. Bring examples of your work that demonstrate your ability to present complex data in an understandable way.
✨Mentorship Matters
As mentoring junior team members is a responsibility, think about your past experiences in guiding others. Be prepared to share how you’ve helped colleagues grow and what your mentoring style is like.
