growth of the portfolio (e.g. R&D teams, Legal, Operations, Risk Management); Technical & Business Leadership : help both the underwriting strategy and the review of the work conducted by Underwriting Data Scientists, providing guidance on technical modeling matters & business requirements. ABOUT YOU EXPERIENCE & QUALIFICATIONS Graduated from a leading academic institution with a degree in mathematics, statistics, data science, physics … or related; 4 years of significant experience minimum (post graduation) in data science or related; As a plus: track record of experience in leading a (small) team and managing business projects; As a plus: prior experience in structuring, pricing & underwriting parametric insurance covers for climate risks. SKILLS Proficiency in Python (e.g. pandas, scikit-learn); Strong background in statistics and More ❯
applications under the guidance of the Senior AI Manager. Role Overview: As an AI Engineer, you will be responsible for developing, deploying, and optimizing AI models while collaborating with data scientists and software engineers. You will work with technologies such as deep learning, embeddings, vector search, and Generative AI to build robust AI-powered solutions. Key Responsibilities: Develop and … optimize AI/ML models with a focus on Generative AI, embeddings, and vector search. Implement deep learning models using frameworks like TensorFlow, PyTorch, or JAX. Collaborate with data scientists to integrate AI models into production systems. Maintain and enhance AI pipelines, ensuring efficiency and scalability. Conduct research on the latest AI advancements and implement innovative solutions. Assist in … regularly reviewing academic literature and research papers. Capable of translating theoretical insights into practical, real-world solutions. Required Qualifications: Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field. 3+ years of experience in AI/ML development. Generative AI experience with Hugging Face, fine-tuning open-source LLMs like Mistral/Llama More ❯
for you if you have: Strong problem solving skills, with an ability to proactively identify challenges and propose solutions An ability to make pragmatic and sensible choices about what data analysis and modelling approaches to use - you can judge when it's right to obsess about the details, and when it's right to ship an MVP as fast More ❯
The Company A fast-scaling RegTech startup is looking for a Senior AI Engineer to help shape and scale its next-generation regulatory change management platform, powered by GenAI and automation. Backed by a major global bank and already working More ❯
We're building a huge technology company that helps make moving country easier. To fulfil our global ambitions, we need extremely ambitious people. We back the ones who step outside the norm. People who find themselves on a different path More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
BDO
Senior Data Scientists – London – Hybrid Job description BDO Regulatory Solutions are currently recruiting for a Senior Data Scientists to join our client, a regulated firm, based in London.We are offering an initial 6 month contract starting as soon as possible with a competitive rate, employed via an Umbrella company. About the role: We are looking for talented and … experienced data scientists with experience to join our programme. Solid knowledge and experience of AI and ML is essential. Key responsibilities include: Design and develop AI/ML based solutions Work with other data scientists to build and deploy production-level solutions Troubleshoot and debug code Work with other teams to understand and solve business problems About you … Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models Machine Learning Deployment: Familiarity with containerised deployment (e.g. Podman, SageMaker, DSW pipelines) Version Control (Git): To maintain reproducible and collaborative workflows Time-Series Analysis: To assess More ❯
