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- 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 work with massive datasets, and a chance to shape analytics.
- Why this job: Join a pioneering team and make impactful decisions in the fast-paced world of finance.
- Qualifications: Degree in STEM, strong skills in statistical modelling, and experience with large datasets.
- Other info: Build an analytics function from scratch in a collaborative, entrepreneurial environment.
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.
- 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. 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.
- 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 in City of London employer: Anonymous
Contact Detail:
Anonymous Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Investments and FinTech in City of London
✨Tip Number 1
Network like a pro! Reach out to people 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 that relate to finance or investments. Use platforms like GitHub to share your code and insights. This will give potential employers a taste of what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with statistical modelling and machine learning. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical folks.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job postings and make sure your application stands out by tailoring it to the specific role and company culture.
We think you need these skills to ace Data Scientist - Investments and FinTech in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Scientist in Investments and FinTech. Highlight your experience with statistical modelling, machine learning, and any relevant projects that showcase your skills in analysing large datasets.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to express your passion for fintech and data analysis. Mention specific experiences that align with the responsibilities listed in the job description, and don’t forget to show your enthusiasm for joining our team.
Showcase Your Technical Skills: Since this role requires strong technical expertise, make sure to list your proficiency in Python, SQL, and any other relevant tools. If you’ve worked with Bayesian modelling or cloud environments, be sure to highlight that too!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for this exciting opportunity in our growing Data and Analytics team!
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 validate and communicate your findings effectively.
✨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 showcase your interest in large-scale data analysis and how it can impact investment decisions.
✨Prepare for Technical Questions
Expect some technical questions around Python, SQL, and possibly Bayesian modelling. Practice coding problems and be ready to explain your thought process. They might even ask you to solve a problem on the spot, so keep your skills sharp!
✨Communicate Clearly
You’ll need to convey complex analytical concepts to both technical and non-technical audiences. Practice explaining your past projects in simple terms, focusing on the insights and recommendations you provided. This will show that you can bridge the gap between data science and business needs.
