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- Tasks: Automate data-quality processes and develop scalable machine-learning pipelines.
- Company: Leading financial services firm collaborating with top investment banks.
- Benefits: Up to £100k salary, hybrid working, and a fantastic benefits package.
- Why this job: Join a growing team and make a real impact in the finance sector.
- Qualifications: 2+ years in Data Science, proficiency in Python & SQL, AWS experience.
- Other info: Exciting career growth opportunities in a dynamic environment.
The predicted salary is between 60000 - 100000 £ per year.
I've partnered with a leader in the Financial Services industry, who are partnered with some of the globe's largest Investment Banks & Trading firms, undertaking a period of growth across their Data team, and are therefore looking to add a highly skilled Data Scientist. My client is looking for a proactive, analytically focused Data Scientist to automate and improve data-quality processes used in the production of aggregated analytical outputs. The role involves transforming an existing prototype into a scalable machine-learning pipeline, replacing a significant amount of manual anomaly detection with robust automated methods.
Responsibilities / Requirements:
- Minimum of 2+ years in a Data Science, ML or Quantitative based role
- Proficiency in Python & SQL
- Experience working with AWS
- Production level experience in ML Model deployment, monitoring and maintenance
- A strong academic background in a highly quantitative field with MSc/PhD's being preferred
- An understanding of the financial services industry, products, quantitative concepts and overall domain knowledge is highly beneficial
Salary: Pays up to £100k depending on skills and experience, along with a great benefits package
Hybrid working: 3-days a week in a Central London office
Interview process: 3-stage interview process
To be considered, you must be UK based and sadly sponsorship isn't available.
Data Scientist - ML - Finance employer: Oliver Bernard
Contact Detail:
Oliver Bernard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - ML - Finance
✨Tip Number 1
Network like a pro! Reach out to connections in the finance and data science sectors. Attend meetups or webinars, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, and machine learning. Share it on platforms like GitHub or even your LinkedIn profile. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for the interview like it’s the final exam! Research the company and its role in the financial services industry. Be ready to discuss how your experience aligns with their needs, especially around automating data processes and ML model deployment.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Data Scientist - ML - Finance
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Data Science, ML, and Python. 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 the financial services industry and how your background makes you a perfect fit for our team. Keep it concise but impactful!
Showcase Your Technical Skills: Since we’re looking for someone with proficiency in Python, SQL, and AWS, make sure to mention specific projects where you’ve used these technologies. We love seeing real-world applications of your skills!
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!
How to prepare for a job interview at Oliver Bernard
✨Know Your Tech Stack
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 machine learning and data quality processes.
✨Showcase Your Financial Knowledge
Since this role is in the financial services industry, it’s crucial to demonstrate your understanding of financial products and quantitative concepts. Prepare examples of how your data science work has impacted financial outcomes or improved processes.
✨Prepare for Technical Questions
Expect technical questions about ML model deployment and monitoring, especially in an AWS environment. Brush up on best practices and be ready to explain your approach to transforming prototypes into scalable solutions.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about their current data challenges or how they envision the evolution of their data team, which will demonstrate your proactive mindset.
