At a Glance
- Tasks: Build and deploy cutting-edge AI products using LLM-based applications.
- Company: Join Harnham, a leader in AI innovation in Greater London.
- Benefits: Flexible working model with 2 days in the office and competitive salary.
- Other info: Dynamic team environment with opportunities for professional growth.
- Why this job: Make a real impact in AI while collaborating with industry experts.
- Qualifications: 5+ years in data science, strong Python and SQL skills, MLOps familiarity.
The predicted salary is between 70000 - 90000 € per year.
Harnham is seeking a Senior Data Scientist in Greater London to join their AI team, focusing on building real AI products. The role involves deploying LLM-based applications, working on end-to-end AI systems, and collaborating closely with stakeholders.
Candidates should have over 5 years of experience in data science, strong skills in Python and SQL, and familiarity with MLOps.
This position offers a flexible working model, with 2 days a week in the office.
Senior Data Scientist, GenAI & Production AI Lead in London employer: Harnham
Harnham is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those passionate about AI and data science. With a flexible working model and opportunities for professional growth, employees are encouraged to collaborate on cutting-edge projects in a supportive environment. Located in Greater London, Harnham offers the unique advantage of being at the heart of a thriving tech hub, making it an ideal place for talented individuals to advance their careers while contributing to meaningful AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist, GenAI & Production AI Lead in London
✨Tip Number 1
Network like a pro! Reach out to people in the AI field, especially those at Harnham or similar companies. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and MLOps. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. We all know technical interviews can be tough, so practice coding challenges and be ready to discuss your past projects in detail.
✨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 are proactive about their job search.
We think you need these skills to ace Senior Data Scientist, GenAI & Production AI Lead in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in data science, especially with LLM-based applications and MLOps. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your background makes you a perfect fit for our team. Let us know what excites you about building real AI products.
Showcase Your Technical Skills:Since we’re looking for strong Python and SQL skills, make sure to mention specific projects or experiences where you’ve used these technologies. We love seeing practical examples of your work!
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 Harnham
✨Know Your AI Stuff
Make sure you brush up on your knowledge of LLM-based applications and end-to-end AI systems. Be ready to discuss specific projects you've worked on that showcase your expertise in deploying AI products.
✨Show Off Your Coding Skills
Since strong skills in Python and SQL are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice common data science challenges beforehand.
✨Understand MLOps
Familiarity with MLOps is key for this role. Be prepared to talk about how you've implemented MLOps practices in your previous work and how they can improve the deployment of AI models.
✨Engage with Stakeholders
Collaboration is crucial, so think about examples where you've successfully worked with stakeholders. Highlight your communication skills and how you’ve translated technical concepts into layman's terms for non-technical team members.
