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- Tasks: Design and implement advanced time-series models for cutting-edge AI systems.
- Company: Leading tech company in Greater London with a focus on innovation.
- Benefits: Competitive salary, remote/hybrid work options, and comprehensive benefits.
- Why this job: Join a pioneering team and shape the future of AI technology.
- Qualifications: PhD in relevant field, expertise in time-series modelling, Deep Learning, and Python.
- Other info: Flexible work environment with opportunities for professional growth.
The predicted salary is between 36000 - 60000 £ per year.
A leading tech company in Greater London is seeking a Time Series Researcher to design and implement foundational time-series models for their advanced AI system, Orbital. The role involves integrating physics into models, managing uncertainty, and ensuring robust production deployment.
Ideal candidates should have:
- A PhD
- Extensive experience with time-series modelling
- Strong skills in Deep Learning and Python
The position offers a remote or hybrid work setup with a competitive salary and benefits.
Remote Time Series Scientist for Production AI employer: Applied Computing
Contact Detail:
Applied Computing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Time Series Scientist for Production AI
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI and time-series fields on LinkedIn. Join relevant groups and participate in discussions to get your name out there and show off your expertise.
✨Tip Number 2
Prepare for those interviews! Brush up on your deep learning and Python skills, and be ready to discuss how you would integrate physics into time-series models. Practice common interview questions and have your own questions ready to show your interest.
✨Tip Number 3
Showcase your work! Create a portfolio of your time-series projects or any relevant research. This can really set you apart from other candidates and give potential employers a taste of what you can bring to the table.
✨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, applying directly shows your enthusiasm and commitment to joining our team.
We think you need these skills to ace Remote Time Series Scientist for Production AI
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with time-series modelling and Deep Learning. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or research!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about integrating physics into AI models and how your background makes you a perfect fit for our team at StudySmarter.
Showcase Your Technical Skills: Since we’re looking for someone with strong Python skills, make sure to mention any specific libraries or frameworks you’ve worked with. We love seeing practical examples of your coding prowess!
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 our team!
How to prepare for a job interview at Applied Computing
✨Know Your Time Series Inside Out
Make sure you brush up on your time-series modelling knowledge. Be prepared to discuss specific models you've worked with, how you integrated physics into them, and the challenges you faced. This will show your depth of understanding and practical experience.
✨Showcase Your Deep Learning Skills
Since the role requires strong skills in Deep Learning, be ready to talk about your experience with relevant frameworks like TensorFlow or PyTorch. Bring examples of projects where you applied these skills, especially in relation to time-series data.
✨Prepare for Technical Questions
Expect technical questions that test your problem-solving abilities. Practice explaining complex concepts clearly and concisely, as you may need to demonstrate your thought process when tackling uncertainty in models.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s approach to production deployment or how they manage uncertainty in their models. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
