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- Tasks: Apply machine learning techniques to solve real-world problems and develop ML software products.
- Company: Leading technology solutions provider in the UK with a focus on innovation.
- Benefits: Collaborative environment, opportunity for professional growth, and interaction with diverse stakeholders.
- Why this job: Make a real impact by driving data-driven insights in a dynamic tech landscape.
- Qualifications: Master’s degree in a relevant field or equivalent experience in machine learning and Python.
- Other info: Engage with cloud platforms and enjoy excellent career development opportunities.
The predicted salary is between 30000 - 50000 £ per year.
A technology solutions provider in the UK is seeking a Data Scientist proficient in machine learning and Python. You will be responsible for applying machine learning techniques to solve real-world problems and work with cloud platforms.
A Master’s degree in a relevant field or equivalent experience is required. Enjoy a collaborative environment with the opportunity to develop industrialized ML software products and interact with various stakeholders to drive data-driven insights.
Data Scientist - ML, Optimization & Production Systems in London employer: Qualient Technology Solutions UK Limited
Contact Detail:
Qualient Technology Solutions UK Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - ML, Optimization & Production Systems 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 dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects and optimisation techniques. This is your chance to demonstrate your expertise in Python and cloud platforms, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. We recommend practising with friends or using mock interview platforms to build your confidence and refine your answers.
✨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 Scientist - ML, Optimization & Production Systems in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning and Python. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
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 team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've applied machine learning techniques to solve real-world problems. We’re looking for practical experience, so share specific instances where you’ve made an impact!
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 the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Qualient Technology Solutions UK Limited
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning concepts and techniques. Be ready to discuss specific algorithms you've used, how they apply to real-world problems, and any projects where you've implemented them. This will show that you’re not just familiar with the theory but can also apply it practically.
✨Show Off Your Python Skills
Since Python is a key requirement for this role, be prepared to demonstrate your coding skills. You might be asked to solve a problem on the spot or explain your code from previous projects. Practising common data manipulation and machine learning libraries like Pandas, NumPy, and Scikit-learn will give you an edge.
✨Understand Cloud Platforms
Familiarise yourself with cloud platforms relevant to machine learning, such as AWS, Azure, or Google Cloud. Be ready to discuss how you’ve used these platforms in past projects, especially in deploying ML models. This shows you can work in a modern tech environment and understand the infrastructure behind your solutions.
✨Engage with Stakeholders
Since the role involves interacting with various stakeholders, think about examples where you've successfully communicated complex data insights to non-technical audiences. Prepare to discuss how you approach collaboration and ensure everyone is on the same page, which is crucial for driving data-driven decisions.
