9 of 9 Remote Amazon SageMaker Jobs in Central London

techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent thinker with a structured approach More ❯

agent solutions that integrate with enterprise systems and cloud platforms. Develop and optimize RESTful and GraphQL APIs to facilitate AI-driven interactions. Utilize AWS services (Lambda, S3, API Gateway, SageMaker, DynamoDB, ECS, etc.) to deploy scalable AI solutions. Implement Full Stack JavaScript (Node.js, React.js, Express, TypeScript, Next.js, etc.) applications to support AI-driven interfaces. Work closely with data scientists More ❯

within large organisations, through e.g. the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning More ❯

performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and contributing to iterative product More ❯

Desirable experience: Familiar with Terraform, from a developer perspective. Previous work in financial services, healthcare, or similarly regulated data environments. Experience with LLMs, voice agents, or tools like AWS SageMaker, AWS Bedrock, or ElevenLabs. Exposure to soft real-time systems or distributed system architectures. Knowledge of OAuth, SQS, or running containers in production. More ❯

data science teams. Ability to build and communicate complex solutions to stakeholders across different levels and disciplines. Proficiency working with modern cloud-based tools (e.g., Azure ML , Databricks , Snowflake , SageMaker , etc.). Deep knowledge of machine learning techniques including predictive modelling, pattern recognition, and optimisation. Strong stakeholder management and product ownership skills. Experience with CI/CD tools such More ❯

in Data Science & ML Expert in Python , data wrangling, EDA, modelling, validation, and deployment Strong in supervised & unsupervised learning ; exposure to NLP/OCR a plus Proficient with AWS SageMaker , Databricks ; Palantir Foundry/AIP is a big plus Insurance/underwriting/claims background is a bonus Confident communicator with client-facing experience 🎯 Interview Process: Round 1: Technical More ❯

miss your chance to secure the future of your career! Contact me @ (url removed) or on (phone number removed). Data Science, Data Scientist, AI, ML, Random Forest, Databricks, SageMaker, Regression, Gradient Boosting, NLP, Palantir, Insurance, Banking More ❯

data extraction ● Deploying models using cloud-based platforms for scalability Key skills we're looking for: ● Strong Python expertise ● Hands-on experience with statistical modelling techniques ● Familiarity with AWS SageMaker, Databricks, and similar tools ● Proficiency in NLP techniques (e.g., text extraction, classification) ● Prior experience deploying predictive models in the insurance domain If this sounds like you, or someone you More ❯