At a Glance
- Tasks: Define the machine learning roadmap and develop innovative ML platforms.
- Company: Engaging Networks, a forward-thinking tech company in the UK.
- Benefits: Competitive salary, flexible working hours, and a charitable gift programme.
- Other info: Join a dynamic team with opportunities for growth and collaboration.
- Why this job: Make a real impact by harnessing data to drive strategic outcomes.
- Qualifications: 2+ years in data science, strong Python skills, and AWS experience.
The predicted salary is between 50000 - 55000 € per year.
Engaging Networks in the UK seeks a Data Scientist responsible for defining the machine learning roadmap and developing ML platforms. You'll harness historical data to generate strategic outcomes, collaborating closely with product and engineering teams.
The ideal candidate has 2+ years in data science, excels in Python, and has experience with AWS. A strong educational background in Statistics or Mathematics is required.
The position offers a competitive salary between £50,000 and £55,000 GBP, alongside benefits including flexible working hours and a charitable gift program.
ML Platform Engineer & Data Scientist (Remote/UK) in London employer: Engaging Networks
Engaging Networks is an exceptional employer that values innovation and collaboration, offering a dynamic work culture where your contributions directly impact meaningful projects. With flexible working hours and a commitment to employee growth through continuous learning opportunities, you will thrive in a supportive environment that encourages creativity and professional development. Located in the UK, this remote position allows you to balance work and life while making a difference in the charitable sector.
StudySmarter Expert Advice🤫
We think this is how you could land ML Platform Engineer & Data Scientist (Remote/UK) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects and data science work. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Brush up on your Python and AWS knowledge, and be ready to discuss how you've used data to drive decisions. Practice makes perfect!
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are excited about joining us. It shows initiative and enthusiasm!
We think you need these skills to ace ML Platform Engineer & Data Scientist (Remote/UK) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in data science and machine learning. We want to see how your skills in Python and AWS shine through, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for the role. Share your passion for data science and how you can contribute to our ML roadmap. Keep it engaging and personal!
Showcase Your Projects:If you've worked on any interesting data science projects, make sure to mention them! We love seeing practical applications of your skills, especially if they relate to machine learning or data analysis.
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 Engaging Networks
✨Know Your ML Roadmap
Before the interview, make sure you understand the machine learning roadmap and how it aligns with the company's goals. Be ready to discuss your vision for developing ML platforms and how your past experiences can contribute to their success.
✨Showcase Your Python Skills
Since Python is a key requirement, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so brush up on your Python knowledge and be ready to explain your thought process as you work through it.
✨Familiarise Yourself with AWS
As experience with AWS is essential, take some time to review the specific services that are relevant to data science. Be prepared to discuss how you've used AWS in previous projects and how it can enhance the ML platforms you’ll be working on.
✨Highlight Your Statistical Background
With a strong educational background in Statistics or Mathematics being crucial, be ready to talk about how your academic knowledge translates into practical applications. Share examples of how you've used statistical methods to drive strategic outcomes in your previous roles.
