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- Tasks: Lead data science projects and perform in-depth performance analysis.
- Company: Major satellite communications company based in London.
- Benefits: Hybrid work options and focus on innovative technology.
- Why this job: Join a cutting-edge team transforming satellite connectivity with AI/ML.
- Qualifications: Degree in a quantitative field and 5+ years of data analysis experience.
- Other info: Exciting opportunities for career growth in a dynamic industry.
The predicted salary is between 43200 - 72000 £ per year.
A major satellite communications company in London is seeking a Data Analyst to perform in-depth performance analysis and lead data science projects. The ideal candidate has a degree in a quantitative discipline and at least 5 years of experience in data analysis, proficient in SQL and Python. The role offers opportunities for hybrid work and focuses on innovative technology in satellite communications.
Senior Data Scientist — AI/ML for Satellite Connectivity in London employer: EUTELSAT SA
Contact Detail:
EUTELSAT SA Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist — AI/ML for Satellite Connectivity in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the satellite communications field on LinkedIn. Join relevant groups and engage in discussions to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those using SQL and Python. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your past projects and how you've used AI/ML in your work. Practice common interview questions with a friend!
✨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 stay updated on new roles.
We think you need these skills to ace Senior Data Scientist — AI/ML for Satellite Connectivity in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data analysis and showcases your skills in SQL and Python. We want to see how your background aligns with the role, so don’t be shy about emphasising relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about satellite communications and how your expertise can contribute to our innovative projects. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any cool data science projects, make sure to mention them! We love seeing real-world applications of your skills, especially if they relate to AI/ML or performance analysis.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at EUTELSAT SA
✨Know Your Data Inside Out
Make sure you brush up on your SQL and Python skills before the interview. Be prepared to discuss specific projects where you've used these tools, especially in relation to performance analysis. This will show that you not only understand the technical side but can also apply it effectively.
✨Showcase Your Experience
With at least 5 years of experience required, be ready to share detailed examples of your past work. Highlight any data science projects you've led, particularly those that involved innovative technology or satellite communications. This will demonstrate your capability and relevance to the role.
✨Understand the Company’s Vision
Research the satellite communications industry and the specific company you're interviewing with. Familiarise yourself with their products and recent developments. This knowledge will help you align your answers with their goals and show genuine interest in the position.
✨Prepare for Technical Questions
Expect to face technical questions related to data analysis and machine learning. Practice explaining complex concepts in simple terms, as you may need to communicate your findings to non-technical stakeholders. This will highlight your ability to bridge the gap between data and decision-making.
