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- Tasks: Create innovative machine learning solutions to enhance financial data and solve user challenges.
- Company: Dynamic financial technology firm in the UK with a focus on innovation.
- Benefits: Flexible remote work, competitive salary, and professional development opportunities.
- Why this job: Join a cutting-edge team and make a real impact in the fintech industry.
- Qualifications: 3+ years in data science, strong Python skills, and ability to explain complex ideas simply.
- Other info: Exciting opportunity for growth in a fast-paced, collaborative environment.
The predicted salary is between 36000 - 60000 £ per year.
A financial technology firm in the UK is seeking a Machine Learning Engineer to bridge data science and software engineering. You will develop production-ready solutions that enhance financial data and solve user problems.
The ideal candidate has over 3 years of experience in data science, strong software practices in Python, and the ability to communicate complex concepts to non-technical stakeholders.
This role offers flexibility with remote work and various professional development benefits.
ML Engineer: Production Data Solutions (Remote) in London employer: Moneyhub
Contact Detail:
Moneyhub Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer: Production Data Solutions (Remote) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the financial tech space on LinkedIn or at industry events. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those that solve real-world problems. This will help you stand out and demonstrate your ability to bridge data science and software engineering.
✨Tip Number 3
Prepare for interviews by brushing up on your Python skills and understanding how to communicate complex concepts simply. Practice explaining your past projects to friends or family who aren’t in tech – it’ll help you nail those tricky interview questions!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace ML Engineer: Production Data Solutions (Remote) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science and software engineering. We want to see how your skills in Python and machine learning can bridge the gap between data and practical solutions.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Share specific examples of how you've solved user problems with your production-ready solutions.
Showcase Communication Skills: Since you'll be communicating complex concepts to non-technical stakeholders, make sure to highlight any relevant experience. We love candidates who can simplify the technical stuff!
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 Moneyhub
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and any relevant machine learning frameworks. Be ready to discuss your past projects in detail, especially how you've developed production-ready solutions. This will show that you can bridge the gap between data science and software engineering.
✨Communicate Like a Pro
Since you'll need to explain complex concepts to non-technical stakeholders, practice simplifying your explanations. Use analogies or real-world examples to make your points clearer. This will demonstrate your ability to communicate effectively, which is crucial for this role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific user problems you've solved in the past using machine learning. Think of examples where your solutions had a tangible impact. This will highlight your practical experience and your ability to enhance financial data.
✨Embrace the Remote Work Culture
Since this position offers remote work flexibility, be ready to talk about how you manage your time and stay productive while working from home. Share any tools or strategies you use to collaborate with teams remotely, as this will show you're a good fit for their work environment.
