Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Automate data processes and build scalable ML pipelines in finance.
- Company: Join a leading recruitment agency for a top Financial Services firm.
- Benefits: Earn up to £100,000 with hybrid working options in Central London.
- Why this job: Make an impact in finance while working with cutting-edge technology.
- Qualifications: 2+ years in data science, proficient in Python, SQL, and AWS.
The predicted salary is between 60000 - 84000 £ per year.
A leading recruitment agency is seeking a highly-skilled Data Scientist for a prominent Financial Services leader in the UK. This role involves automating and improving data-quality processes, transforming prototypes into scalable ML pipelines.
Ideal candidates have:
- At least 2 years of experience
- Proficiency in Python and SQL
- Experience with AWS
The position offers a salary of up to £100,000 and hybrid working arrangements in Central London.
Finance Data Scientist: ML Pipelines & Python/AWS in England employer: Oliver Bernard
Contact Detail:
Oliver Bernard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Finance Data Scientist: ML Pipelines & Python/AWS in England
✨Tip Number 1
Network like a pro! Reach out to professionals in the finance and data science sectors on LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Showcase your skills! Create a portfolio of your projects, especially those involving ML pipelines and AWS. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss how you've automated processes or improved data quality in past roles.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find and apply for roles that match your skills and experience. Plus, we’re here to support you every step of the way!
We think you need these skills to ace Finance Data Scientist: ML Pipelines & Python/AWS in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and AWS. We want to see how your skills align with the role of a Finance Data Scientist, so don’t hold back on 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 data science in finance and how you can contribute to automating and improving data-quality processes at StudySmarter.
Showcase Your Projects: If you've worked on any ML pipelines or data quality improvements, make sure to mention them! We love seeing real-world applications of your skills, so include links to your GitHub or any relevant portfolios.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
How to prepare for a job interview at Oliver Bernard
✨Know Your Tech Inside Out
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss specific projects where you've used these languages, especially in relation to ML pipelines and AWS. This will show that you not only understand the theory but can also apply it practically.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've automated data-quality processes in the past. Think of examples where you identified a problem, implemented a solution, and the impact it had. This will demonstrate your ability to think critically and improve existing systems.
✨Familiarise Yourself with the Company
Research the financial services leader you're interviewing with. Understand their products, services, and any recent news. This knowledge will help you tailor your answers and show genuine interest in the role and the company.
✨Ask Insightful Questions
Prepare thoughtful questions to ask at the end of the interview. Inquire about their current data challenges or how they envision the future of their ML pipelines. This not only shows your enthusiasm but also your strategic thinking regarding the role.
