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- Tasks: Work with large data sets and develop insights using Python.
- Company: Be-IT is a dynamic data and insights consultancy.
- Benefits: Enjoy hybrid working and competitive pay of £450-500 per day.
- Why this job: Join a forward-thinking team and make an impact in data development.
- Qualifications: Proficiency in Python and experience with AWS are essential.
- Other info: Contract role running until December 2025, outside IR35.
Be-IT are seeking a contract Data Scientist/Python Developer for a data and insights consultancy. Starting ASAP until Dec 2025 Outside IR35 £450-500 per day Hybrid working at the Bath office.
They are seeking python skills, experience working with large data sets and AWS. It's a data and development role.
Sounds like you? Apply online to learn more.
Data Scientist/Python Developer employer: Be-IT Resourcing
Contact Detail:
Be-IT Resourcing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist/Python Developer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, particularly Python and AWS. Having hands-on experience or projects that showcase your skills in these areas can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the data science field, especially those who work with data and insights consultancies. Attend relevant meetups or webinars to make connections and learn more about the industry, which could give you an edge during interviews.
✨Tip Number 3
Prepare for technical interviews by practising coding challenges and data manipulation tasks in Python. Websites like LeetCode or HackerRank can be great resources to sharpen your skills and boost your confidence.
✨Tip Number 4
Research Be-IT and their projects to understand their approach to data science and consultancy. Tailoring your discussions during interviews to reflect your knowledge of their work can demonstrate your genuine interest in the role and the company.
We think you need these skills to ace Data Scientist/Python Developer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python skills and experience with large data sets. Include specific projects or roles where you've used AWS, as this is crucial for the position.
Craft a Compelling Cover Letter: In your cover letter, explain why you're interested in the Data Scientist/Python Developer role. Mention your relevant experience and how it aligns with the consultancy's needs, particularly in data and development.
Showcase Relevant Projects: If you have worked on any significant projects involving data analysis or Python development, summarise these in your application. Highlight your contributions and the impact of your work.
Proofread Your Application: Before submitting, carefully proofread your application for any errors or typos. A polished application reflects your attention to detail, which is essential in data roles.
How to prepare for a job interview at Be-IT Resourcing
✨Showcase Your Python Skills
Be prepared to discuss your experience with Python in detail. Bring examples of projects where you've used Python to manipulate large datasets or develop data-driven applications. This will demonstrate your technical proficiency and problem-solving abilities.
✨Familiarise Yourself with AWS
Since the role requires experience with AWS, make sure you understand the key services relevant to data science, such as S3, EC2, and Lambda. Be ready to explain how you've used these services in past projects or how you would approach using them in this role.
✨Prepare for Technical Questions
Expect technical questions that assess your understanding of data science concepts and Python programming. Brush up on algorithms, data structures, and statistical methods. Practising coding challenges can also help you feel more confident.
✨Demonstrate Your Problem-Solving Approach
During the interview, be prepared to walk through your thought process when tackling data-related problems. Employers appreciate candidates who can articulate their approach to analysing data, drawing insights, and making data-driven decisions.
