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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 shape analytics function, and work with massive datasets.
- Why this job: Join a high-impact role in fintech, making real contributions to investment decisions.
- Qualifications: Degree in STEM, strong skills in statistical modelling, and experience with large datasets.
- Other info: Collaborative environment 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.
- 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 Slough employer: Anonymous
Contact Detail:
Anonymous Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Investments and FinTech in Slough
✨Tip Number 1
Network like a pro! Reach out to people in the fintech space, especially those working in data science. Attend meetups or webinars, and don’t be shy about asking for informational interviews. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those relevant to finance. Use platforms like GitHub to share your code and insights. This will give potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data science and fintech. 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 Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Data Scientist role. Highlight your expertise in statistical modelling, machine learning, and any relevant projects you've worked on in fintech or financial services.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how you can contribute to our team. Mention specific technologies or methodologies you’ve used, especially those related to Bayesian modelling and large-scale data analysis.
Showcase Your Technical Skills: Don’t forget to include your proficiency in Python and SQL in your application. We love seeing examples of how you've applied these skills in real-world scenarios, so feel free to share any relevant projects or achievements.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the quickest way for us to see your application and get you into the process!
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 relation to large datasets. The interviewers will want to see that you can not only talk the talk but also walk the walk.
✨Show Your Passion for FinTech
Since this role is in a fintech environment, it’s crucial to demonstrate your enthusiasm for the industry. Research the company and its products, and be prepared to discuss how your background aligns with their mission. Share any personal projects or experiences that highlight your interest in financial services.
✨Communicate Clearly
You’ll need to explain complex analytical concepts to both technical and non-technical audiences. Practice articulating your thoughts clearly and concisely. Use examples from your past work to illustrate how you’ve successfully communicated insights to stakeholders.
✨Familiarise Yourself with Tools and Technologies
Get comfortable with the tools mentioned in the job description, like Python libraries and SQL. If you have experience with cloud environments or collaborative development tools, be ready to discuss how you've used them in your previous roles. Showing familiarity with these technologies will give you an edge.