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- Tasks: Leverage AI and machine learning to drive business insights in FinTech.
- Company: Leading FinTech firm based in Birmingham with a focus on innovation.
- Benefits: Competitive salary, 25 days holiday, and flexible hybrid working.
- Why this job: Join a dynamic team and make an impact using advanced analytics.
- Qualifications: Strong skills in statistical modelling, Python, AWS, and SQL required.
- Other info: Collaborative environment with opportunities for professional growth.
The predicted salary is between 28800 - 48000 £ per year.
A leading FinTech firm in Birmingham is looking for a Data Scientist to leverage advanced analytics and machine learning to drive business insights. You'll lead the use of AI within the data team, working closely with engineering and product teams to implement data-driven strategies.
The role demands strong skills in statistical modelling, Python, AWS, and SQL.
This position offers a competitive salary, 25 days of holiday, and a flexible hybrid working environment.
Data Scientist - AI/ML for FinTech, Remote/Hybrid in Birmingham employer: Thyme
Contact Detail:
Thyme Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - AI/ML for FinTech, Remote/Hybrid in Birmingham
✨Tip Number 1
Network like a pro! Reach out to folks in the FinTech space, especially those working with AI and machine learning. A friendly chat can open doors and give us insights into the company culture.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your projects in statistical modelling, Python, and AWS. We want to see how you’ve used these tools to drive business insights.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your SQL queries and machine learning concepts. We can help you with mock interviews to boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to connect directly with us.
We think you need these skills to ace Data Scientist - AI/ML for FinTech, Remote/Hybrid in Birmingham
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with statistical modelling, Python, AWS, and SQL. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI/ML in FinTech and how you can contribute to our data team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects: If you've worked on any cool projects involving AI or machine learning, make sure to mention them! We’re keen to see real-world applications of your skills, so include links or descriptions that demonstrate your expertise.
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. Plus, it’s super easy – just follow the prompts and you’ll be all set!
How to prepare for a job interview at Thyme
✨Know Your Tech Stack
Make sure you brush up on your skills in Python, AWS, and SQL. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Showcase Your Statistical Modelling Skills
Prepare to explain your approach to statistical modelling. Bring examples of how you've applied these techniques in real-world scenarios, especially in the context of FinTech, to demonstrate your expertise.
✨Understand the Business Context
Research the company and its products. Understand how data science can drive insights in the FinTech sector. This will help you align your answers with their business goals during the interview.
✨Prepare for Collaborative Questions
Since you'll be working closely with engineering and product teams, be ready to discuss your experience in cross-functional collaboration. Think of examples where you successfully worked with others to implement data-driven strategies.
