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- Tasks: Collaborate to validate data, deploy ML pipelines, and enhance software applications.
- Company: Leading engineering services provider in the UK with an empowering culture.
- Benefits: Entry-level position with opportunities for innovation and growth.
- Why this job: Make a real impact by contributing to cutting-edge data science solutions.
- Qualifications: Experience in data science methods and statistical analysis.
- Other info: Temporary role with a chance to work in a dynamic environment.
The predicted salary is between 28800 - 48000 £ per year.
A leading engineering services provider in the United Kingdom is seeking a Data Science Engineer. The role involves collaboration with teams to validate and interpret data, deploy machine learning pipelines, and enhance customer software applications.
Ideal candidates will have experience in data science methods and statistical analysis. This entry-level, temporary position offers a chance to contribute to innovative solutions within an empowering workplace culture.
Data Science Engineer: Build ML Pipelines & Insights in London employer: Quest Global
Contact Detail:
Quest Global Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Engineer: Build ML Pipelines & Insights in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the data science field on LinkedIn or at local meetups. We can’t stress enough how valuable personal connections can be in landing that Data Science Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning pipelines and data analysis. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and practical tests. We recommend practising with friends or using online resources to simulate the interview experience.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Science Engineer: Build ML Pipelines & Insights in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data science methods and statistical analysis. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or coursework!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Data Science Engineer position and how you can contribute to our innovative solutions. Keep it concise but impactful!
Showcase Your Collaboration Skills: Since this role involves working with teams, mention any past experiences where you collaborated effectively. We love seeing candidates who can work well with others to validate and interpret data.
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 Quest Global
✨Know Your Data Science Basics
Make sure you brush up on fundamental data science methods and statistical analysis techniques. Be ready to discuss how you've applied these in past projects or coursework, as this will show your understanding and readiness for the role.
✨Showcase Your ML Pipeline Experience
If you've worked on any machine learning pipelines, be prepared to explain your process. Discuss the tools you used, the challenges you faced, and how you overcame them. This will demonstrate your practical knowledge and problem-solving skills.
✨Collaborate and Communicate
Since the role involves collaboration with teams, think of examples where you've successfully worked with others. Highlight your communication skills and how you can interpret and validate data in a team setting. This will show that you're a good fit for their workplace culture.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company’s projects or their approach to data science. This not only shows your interest in the role but also gives you a chance to assess if the company aligns with your career goals.
