Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop and validate models for analysing non-performing loan portfolios using cutting-edge technology.
- Company: Dynamic fintech platform backed by a global investment firm, focused on innovation.
- Benefits: Competitive salary, opportunity to build analytics from scratch, and work with massive datasets.
- Why this job: Join a high-impact role that shapes investment decisions in a fast-paced environment.
- Qualifications: Degree in STEM, strong statistical modelling skills, and proficiency in Python and SQL.
- Other info: Collaborative culture with opportunities for professional growth and development.
The predicted salary is between 36000 - 60000 £ per year.
We are working with a growing consumer finance fintech platform, who are looking to build out their Data and Analytics department. The team, who have recently received backing from a global Investment firm are now building out a Data and Analytics team in London - with a focus on supporting their Unsecured NPL Portfolio Investment team. This role is ideal for a technically strong, quantitatively minded professional with a background in statistics and data science, looking to apply their skills in financial services. While specific NPL experience is not required, a passion for large-scale data analysis and modern analytics frameworks is essential. You will work in a neo-bank/fintech-style environment, using cutting-edge technology to analyze terabytes of data and support high-impact investment decisions.
Responsibilities
- Develop, implement, and validate statistical and machine learning models for analysing non-performing loan portfolios.
- Collaborate with cross-functional teams—including credit, collections, and data engineering—to translate business objectives into robust analytical solutions.
- Build software using modern technology to enable investing and asset management at scale.
- Apply Bayesian modelling and probabilistic programming techniques to address uncertainty and improve prediction accuracy.
- Analyse large-scale datasets to identify key drivers, trends, and early warning signals within NPL portfolios.
- Clearly communicate model results, insights, and recommendations to stakeholders, including both technical and non-technical audiences.
- Stay current with advances in statistical modelling, machine learning, and data science, continuously evaluating and integrating new techniques and tools.
Requirements
- University degree in a STEM field (e.g., Mathematics, Statistics, Computer Science, Engineering, Physics, Economics); advanced degree preferred.
- Strong expertise in statistical modelling, Bayesian inference, and machine learning.
- Proficient in Python (using libraries such as NumPy, pandas, scikit-learn, PyMC or Stan).
- Experienced in SQL with the ability to write efficient and robust queries.
- Demonstrated experience working with large and complex datasets.
- Ability to communicate complex analytical concepts clearly and effectively to a range of audiences.
- Experience with model governance, documentation, and deployment best practices.
- Experience with cloud environments (e.g., AWS Sagemaker).
- Experience with collaborative development tools (e.g., Git, JIRA) is a plus.
- Prior experience in financial services, banking, or credit risk modelling is beneficial.
- 5-8 years experience in a Data/Analytics role, ideally within a Financial Institution.
Why This Role
- Opportunity to build an analytics function from the ground up in a cutting-edge, entrepreneurial environment.
- Work with massive datasets and modern tools at the forefront of fintech innovation.
- High-impact role directly contributing to investment and portfolio decision-making.
Data Scientist - Investments and FinTech employer: Anonymous
Contact Detail:
Anonymous Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Investments and FinTech
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech and data science space on LinkedIn. Join relevant groups, attend meetups, 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 data analysis projects, especially those related to finance or machine learning. This is your chance to demonstrate your expertise in Python and statistical modelling, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding of the fintech landscape. Be ready to discuss how you would tackle real-world problems, like analysing non-performing loan portfolios. Practice explaining complex concepts in simple terms!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who are passionate about data and analytics. Your next big opportunity could be just a click away, so get your application in!
We think you need these skills to ace Data Scientist - Investments and FinTech
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your expertise in statistical modelling, machine learning, and any relevant projects you've worked on. We want to see how you can bring value to our Data and Analytics team!
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 the fintech space. Share specific examples of how you've tackled large datasets or developed models that made an impact. Let us know why you're excited about this role!
Showcase Your Technical Skills: Since we're looking for someone with strong technical abilities, make sure to mention your proficiency in Python, SQL, and any experience with cloud environments. If you've used tools like Git or JIRA, don't forget to include that too. We love seeing candidates who are up-to-date with modern technology!
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 gives you a chance to explore more about our company culture and values!
How to prepare for a job interview at Anonymous
✨Know Your Data Science Stuff
Make sure you brush up on your statistical modelling and machine learning techniques. Be ready to discuss how you've applied these skills in real-world scenarios, especially in financial contexts. They’ll want to see that you can not only build models but also understand the underlying principles.
✨Show Your Passion for FinTech
Even if you don’t have direct experience with non-performing loans, demonstrate your enthusiasm for the fintech space. Talk about any relevant projects or experiences that highlight your interest in large-scale data analysis and how it can impact investment decisions.
✨Communicate Clearly
Prepare to explain complex analytical concepts in simple terms. You might be talking to stakeholders who aren’t as technical, so practice how you’d present your findings and recommendations. Use examples from past experiences to illustrate your points.
✨Familiarise Yourself with Tools
Since they’re looking for someone proficient in Python and SQL, make sure you’re comfortable discussing your experience with these tools. If you’ve worked with cloud environments like AWS or collaborative tools like Git, be ready to share how you’ve used them in your previous roles.
