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- Tasks: Develop and deploy predictive models to transform consumer credit risk assessment.
- Company: Join a progressive fintech credit startup making waves in financial inclusion.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Why this job: Make a real impact on underserved consumers with ethical data science.
- Qualifications: Degree in a quantitative field and 2+ years in Fintech or Credit Risk.
- Other info: Work in a fast-paced startup with expert leadership and autonomy.
The predicted salary is between 36000 - 60000 £ per year.
You will develop and deploy innovative predictive models to transform consumer credit risk assessment. By balancing foundational statistics with advanced machine learning and Generative AI, you will tackle challenges in affordability, fraud detection, and entity resolution. Your work directly impacts underserved consumers by creating more equitable financial products through explainable data science.
Location: London, UK
Why this role is remarkable:
- Rare opportunity to combine traditional linear regression stability with cutting-edge XGBoost and LLM applications in a high-stakes production environment.
- Join a fast-moving, well-funded startup backed by expert leadership where you have the autonomy to lead projects from experimentation to containerized deployment.
- Directly contribute to financial inclusion by building ethical models that use SHAP for transparency, ensuring fair outcomes for everyday consumers.
What you will do:
- Build and maintain foundational linear models and advanced XGBoost architectures for credit, affordability, and fraud scoring.
- Implement NLP techniques and LLM context engineering for large-scale entity resolution and unstructured data analysis.
- Collaborate with engineering teams on MLOps to containerize and monitor models within a high-scale AWS cloud environment.
The ideal candidate:
- Holds a degree in a quantitative field with 2+ years of professional experience in Fintech, Finance, or Credit Risk.
- Demonstrates expert-level Python skills and a deep understanding of statistical assumptions, model interpretability, and bias mitigation.
- Possesses a creative, analytical mindset capable of identifying behavioral clusters and trends within raw, complex datasets without predefined hypotheses.
Data Scientist and AI Engineer at progressive fintech credit startup in London employer: Jack & Jill/External Ats
Contact Detail:
Jack & Jill/External Ats Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist and AI Engineer at progressive fintech credit startup in London
✨Tip Number 1
Get to know Jack! He’s your go-to AI for understanding your skills and career goals. Chat with him on our website to get personalised advice and find the best opportunities tailored just for you.
✨Tip Number 2
Don’t underestimate the power of networking! Connect with professionals in the fintech space, attend meetups, and engage on platforms like LinkedIn. You never know who might have a lead on your dream job!
✨Tip Number 3
Prepare for your chat with Jill! Research the company and role thoroughly so you can showcase your knowledge and enthusiasm. This will help you stand out when she’s considering candidates for the position.
✨Tip Number 4
Follow up after your conversation! A quick thank-you note or message can leave a lasting impression. It shows your interest and professionalism, which can set you apart from other candidates.
We think you need these skills to ace Data Scientist and AI Engineer at progressive fintech credit startup in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python expertise and any experience with predictive models. We want to see how you can balance traditional methods with cutting-edge techniques like XGBoost and LLM applications.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon and get straight to the point about your experience and how it relates to the role.
Tailor Your Application: Don’t just send a generic application! Customise it to reflect how your background aligns with our mission of financial inclusion and ethical model building. Show us why you’re the perfect fit for this role.
Apply Through Our Website: Remember to apply through our website! It’s the best way for us to connect you with Jack and ensure your application gets the attention it deserves. Let’s make this happen!
How to prepare for a job interview at Jack & Jill/External Ats
✨Know Your Models Inside Out
Make sure you can discuss both foundational linear models and advanced techniques like XGBoost. Be ready to explain how these models work, their applications in credit risk assessment, and how you’ve used them in past projects.
✨Showcase Your Python Skills
Prepare to demonstrate your expert-level Python skills. Bring examples of code you've written or projects you've completed that highlight your ability to implement machine learning algorithms and handle complex datasets.
✨Understand the Importance of Explainability
Since this role focuses on ethical models and transparency, be prepared to discuss how you would use SHAP for model interpretability. Share any experiences where you’ve had to ensure fairness in your models.
✨Collaborate and Communicate
This position involves working closely with engineering teams. Think of examples where you’ve successfully collaborated on MLOps or similar projects. Highlight your communication skills and how you ensure everyone is on the same page.
