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- Tasks: Develop and optimise machine learning models while analysing business problems.
- Company: Leading data science solutions provider in the UK.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a dynamic team and make an impact with cutting-edge data solutions.
- Qualifications: Master's degree in data science or related fields; proficient in Python and AWS.
- Other info: Collaborative environment with strong focus on innovation and career advancement.
The predicted salary is between 36000 - 60000 £ per year.
A data science solutions provider in the UK is seeking a Data Scientist responsible for developing and optimizing machine learning models. The role includes analyzing business problems, building data processing pipelines, and engaging with stakeholders to gather requirements.
Candidates should have a Master's degree in data science or related fields and be proficient in Python and cloud solutions, particularly AWS. Strong analytical and data engineering skills are essential for success in this role.
Production Data Scientist & ML Engineer employer: ixceed solutions
Contact Detail:
ixceed solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Production Data Scientist & ML Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts on LinkedIn. 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 machine learning models and data processing pipelines. This is your chance to demonstrate your analytical prowess and technical skills in Python and AWS.
✨Tip Number 3
Prepare for those interviews! Brush up on common data science questions and be ready to discuss how you've tackled real-world business problems. Practising with mock interviews can really boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team!
We think you need these skills to ace Production Data Scientist & ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning models and data processing pipelines. We want to see how your skills in Python and AWS can shine through!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you're the perfect fit for the role. Share specific examples of how you've tackled business problems and engaged with stakeholders in the past.
Showcase Your Analytical Skills: In your application, don’t forget to mention any projects or experiences that demonstrate your strong analytical and data engineering skills. We love seeing how you approach problem-solving!
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’re considered for this exciting opportunity!
How to prepare for a job interview at ixceed solutions
✨Know Your Models
Make sure you can discuss the machine learning models you've worked with in detail. Be prepared to explain how you developed and optimised them, as well as the business problems they solved. This shows your practical experience and understanding of the role.
✨Showcase Your Python Skills
Since proficiency in Python is crucial, brush up on your coding skills before the interview. You might be asked to solve a problem on the spot or discuss your previous projects. Having examples ready will demonstrate your expertise and confidence.
✨Understand Cloud Solutions
Familiarise yourself with AWS and any other cloud solutions relevant to the role. Be ready to discuss how you've used these platforms in your past work, especially in building data processing pipelines. This will highlight your technical capabilities and readiness for the job.
✨Engage with Stakeholders
Prepare to talk about your experience working with stakeholders to gather requirements. Think of specific examples where you successfully translated business needs into data science solutions. This will show your ability to communicate effectively and collaborate with others.