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Uncapped

Uncapped

www.weareuncapped.com

2 Jobs

80 Employees

About the Company

Founded in 2019, Uncapped provides working capital lines from PS10k to PS10m to growing brands, retailers and sellers allowing founders to access fair and flexible finance.

In those 4 years, Uncapped have become a leading alternative finance provider and empowered thousands of ambitious companies to turbocharge growth through non-dilutive capital allowing them to fund inventory, marketing and all other growth needs all while retaining full control and ownership of their business.

Want to find out how we can help scale your business? Get in touch today

Listed Jobs

Company background Company brand
Company Name
Uncapped
Job Title
Head of Credit Strategy and Analytics
Job Description
**Job title:** Head of Credit Strategy and Analytics **Role Summary:** Lead the Credit Strategy and Analytics function for a small‑ticket lending portfolio, designing and executing data‑driven credit models that incorporate unconventional data sources. Build a high‑performing analytics team, collaborate across sales, operations, engineering, product and external partners, and provide analytical leadership to business units such as marketing, pricing, segmentation, product development and customer experience. **Expactations:** * 10‑15 years of experience in analytical credit risk management within fintech or banking, with a focus on consumer or SME lending. * At least 5 years in senior managerial or leadership roles. * Proven expertise in data analysis, credit strategy development, advanced data‑science techniques, and machine learning. * Demonstrated ability to manage and grow a team of analysts, mentor talent, and drive measurable business impact. **Key Responsibilities:** 1. Design and implement a comprehensive credit risk management and analytics framework for the small‑business lending portfolio. 2. Oversee development and deployment of advanced credit risk models, collaborating with data scientists, data engineering, decision science, and ML‑Ops teams. 3. Analyse structured and unstructured data from varied sources, including unconventional datasets, and design experiments to gather additional data when needed. 4. Ensure continuous model performance monitoring, validation, and refinement in live environments. 5. Lead cross‑functional initiatives in risk‑based pricing, marketing, product development, and customer experience. 6. Provide analytical leadership across the organization, translating complex insights into actionable strategies. 7. Build and maintain strong relationships with Sales, Operations, Engineering, Product, and external partners. 8. Mentor and develop the analytics team, ensuring high‑quality outputs aligned with strategic goals. **Required Skills:** * Strong analytical and quantitative aptitude. * Deep knowledge of advanced machine learning techniques and credit risk modeling. * Proficient in SQL and Python with hands‑on coding experience. * Experience managing and scaling analytics teams. * Excellent communication skills, able to present complex concepts clearly to diverse stakeholders. * Innovative mindset for exploring and leveraging unconventional data sources. **Required Education & Certifications:** * Minimum 3‑year bachelor’s degree (or equivalent) in Statistics, Mathematics, Econometrics, Data Science, Physics, or a related quantitative field; or * Full 2‑year master’s degree (or equivalent) in the same disciplines. * Short or accelerated postgraduate programs (e.g., 1‑year master’s) are not acceptable.
London, United kingdom
Hybrid
Senior
02-12-2025
Company background Company brand
Company Name
Uncapped
Job Title
Data Scientist
Job Description
**Job title** Data Scientist **Role Summary** Design, develop, and implement advanced machine learning and AI models focused on credit risk and related business use cases. Lead the full model lifecycle, from data ingestion to deployment, and collaborate across product, engineering, and risk teams to align ML solutions with business and regulatory goals. **Expactations** - Manage end‑to‑end model development and production deployment, maintaining high accuracy and relevance. - Drive and maintain an ML Ops framework that supports continuous integration, continuous delivery, and model monitoring. **Key Responsibilities** - Build predictive models using statistical techniques and modern AI approaches (LLMs, neural nets). - Define and implement an ML Ops pipeline: data ingestion, transformation, training, deployment, and monitoring. - Collaborate with commercial, product, and risk stakeholders to embed ML insights into new products and customer segments. - Monitor model performance, troubleshoot issues, and iterate to improve accuracy. - Mentor junior data scientists and share best practices across the organization. - Document processes, model rationales, and deployment guidelines. **Required Skills** - 5+ years in data science with hands‑on ML model development and production deployment. - Expert knowledge of statistical modeling, predictive analytics, and deep learning. - Strong coding in Python, SQL, and frameworks like PyTorch or TensorFlow. - Experience with ML Ops tools (MLflow, Kubeflow, Vertex AI) and CI/CD pipelines. - Excellent communication with both technical and non‑technical stakeholders. - Familiarity with financial services, particularly lending and credit risk, is advantageous. **Required Education & Certifications** - Ph.D. in Mathematics, Physics, Statistics, AI, or a closely related field. - Relevant certifications in data science, machine learning, or software engineering are a plus.
London, United kingdom
Hybrid
Mid level
28-01-2026