At a Glance
- Tasks: Lead the development of AI-driven solutions to prevent ad waste and enhance product capabilities.
- Company: A forward-thinking tech firm focused on data-driven innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Exciting role with potential for impactful contributions in a collaborative environment.
- Why this job: Join a dynamic team at the forefront of AI and data science.
- Qualifications: Strong ML experience, proficiency in Python and SQL, and AWS knowledge.
The predicted salary is between 60000 - 80000 € per year.
A data-driven technology firm is looking for a Senior Data Scientist to help build new capabilities within ad waste prevention. You will work at the intersection of data science, AI, and product development to create scalable solutions.
The ideal candidate has strong experience in ML systems, proficiency in Python and SQL, and practical knowledge of AWS. This full-time role is based in Greater London and offers a hybrid work format.
Senior Data Scientist - AI, Production ML & POC Lead in London employer: Lunio
Join a forward-thinking data-driven technology firm in Greater London, where innovation meets collaboration. We pride ourselves on fostering a dynamic work culture that encourages creativity and continuous learning, offering ample opportunities for professional growth in the rapidly evolving fields of AI and machine learning. With a hybrid work format, you can enjoy the flexibility of remote work while being part of a passionate team dedicated to making a meaningful impact in ad waste prevention.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist - AI, Production ML & POC Lead in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that Senior Data Scientist role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving Python and SQL. We want to see your practical knowledge in action, so make sure it’s easy to access and visually appealing.
✨Tip Number 3
Prepare for the interview by brushing up on your AWS knowledge. We recommend going through common interview questions related to cloud services and ML systems. Being well-prepared will help you stand out as a candidate.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior Data Scientist - AI, Production ML & POC Lead in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with ML systems, Python, SQL, and AWS in your application. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application:Take a moment to customise your CV and cover letter for this specific role. Mention how your past experiences relate to ad waste prevention and product development – it’ll make you stand out!
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon unless it’s relevant to the role.
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!
How to prepare for a job interview at Lunio
✨Know Your Data Science Fundamentals
Brush up on your core data science concepts, especially around machine learning systems. Be ready to discuss your experience with algorithms, model evaluation, and how you've applied these in real-world scenarios.
✨Showcase Your Technical Skills
Since proficiency in Python and SQL is key for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice common data manipulation tasks and SQL queries beforehand.
✨Familiarise Yourself with AWS
As practical knowledge of AWS is essential, make sure you can talk about your experience with cloud services. Be prepared to discuss how you've used AWS tools in your previous projects, particularly in relation to deploying ML models.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world situations. Think of examples where you've successfully implemented scalable solutions or prevented ad waste, and be ready to explain your thought process.
