At a Glance
- Tasks: Design GenAI workflows and develop predictive ML models in a dynamic fintech environment.
- Company: Join a leading UK fintech known for innovation and cutting-edge technology.
- Benefits: Competitive salary package and the chance to work on groundbreaking AI applications.
- Other info: Hybrid working model with opportunities for professional growth.
- Why this job: Make an impact in the fintech space with your GenAI expertise and creativity.
- Qualifications: Experience in building LLM-powered applications and strong Python skills required.
The predicted salary is between 70000 - 90000 € per year.
Burns Sheehan is partnering with a leading UK fintech to find a Senior Data Scientist with hands-on GenAI experience. The role involves designing GenAI workflows, building evaluation frameworks, and developing predictive ML models.
Candidates should have experience in building LLM-powered applications, strong Python skills, and the ability to translate business problems into technical solutions.
This position offers the opportunity to work on cutting-edge AI applications with a competitive salary package.
Senior GenAI Data Scientist — Fintech, Hybrid London employer: Burns Sheehan
At Burns Sheehan, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London-based team enjoys a hybrid working model, competitive salary packages, and ample opportunities for professional growth in the rapidly evolving fintech sector. Join us to be at the forefront of AI technology while contributing to meaningful projects that make a real impact.
StudySmarter Expert Advice🤫
We think this is how you could land Senior GenAI Data Scientist — Fintech, Hybrid London
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech space, especially those working with GenAI. A casual chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your GenAI projects and predictive ML models. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your Python skills and understanding how to translate business problems into technical solutions. Practice common interview questions related to data science and GenAI.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting roles, and applying directly can sometimes give you an edge. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Senior GenAI Data Scientist — Fintech, Hybrid London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your hands-on GenAI experience and any relevant projects you've worked on. We want to see how your skills in building LLM-powered applications can shine through!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you're the perfect fit for this role. Share specific examples of how you've translated business problems into technical solutions, and don't forget to mention your strong Python skills!
Showcase Your Projects:If you've developed predictive ML models or designed GenAI workflows, make sure to include these in your application. We love seeing real-world applications of your skills, so don’t hold back!
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 this exciting opportunity in the fintech space!
How to prepare for a job interview at Burns Sheehan
✨Know Your GenAI Inside Out
Make sure you brush up on your GenAI knowledge before the interview. Be ready to discuss your hands-on experience with GenAI workflows and LLM-powered applications. Prepare examples of how you've designed these systems and the impact they had on previous projects.
✨Showcase Your Python Skills
Since strong Python skills are a must, be prepared to demonstrate your coding abilities. You might be asked to solve a problem on the spot or explain your thought process behind a piece of code. Practise common data science libraries like Pandas and NumPy to show you're up to speed.
✨Translate Business Problems into Tech Solutions
Think about how you've tackled business challenges in the past. Be ready to explain how you identified a problem, developed a predictive ML model, and what the outcomes were. This will show your ability to bridge the gap between technical and business needs.
✨Prepare Questions for Them
Interviews are a two-way street! Prepare insightful questions about their current projects, team dynamics, and future goals in AI. This not only shows your interest but also helps you gauge if the company is the right fit for you.
