4 of 4 Big Data Jobs in Oxford

Responsibilities Designing, developing, and maintaining high-performance, scalable, and secure backend services and APIs using technologies such as Python and NodeJS. Collaborating with science teams, full stack engineers, and data engineers to understand data requirements and integrate user needs into backend services. Building and maintaining RESTful APIs to surface data in the platform, ensuring it is findable … and accessible in line with FAIR principles. Developing APIs that support future interoperability and federation for pathogen diagnostics, epidemiology monitoring, and research. Working with data engineers to build pipelines and processes that store and transform platform data for easy consumption. Implementing and managing data storage solutions including data lakes, data warehouses, and databases such as … object storage, Oracle Autonomous Database, and PostgreSQL. Supporting innovation efforts by exploring new technologies such as vector databases to enable search and AI use cases. Using big data technologies like Kafka, Iceberg, and Parquet, along with managed databases including PostgreSQL and Oracle vector databases. Operating, monitoring, and maintaining Oracle Cloud infrastructure to ensure backend services are highly available More ❯

and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for gaining insight into real-world datasets and clearly communicating through data visualization techniques Interest in material discovery, computer vision, handling big data and optimisation techniques Highly effective communicator who encourages innovation through collaboration Natural problem-solver with a More ❯

and supporting ML models in production Excellent communicator across technical teams and stakeholders Effective problem-solver who takes initiative in complex production settings Experience with scientific computing, deep learning, big data, or health IT ontologies (e.g., PyTorch, JAX, Spark, HL7, FHIR) (desirable) Familiarity with cloud infrastructure (Azure/AWS), infrastructure as code, Kubernetes, Linux, Docker, data pipelines More ❯

Assess the practicality and relevance of modern technologies such as machine learning, big data analytics, generative AI, multi-agent systems, and quantum computing in insurance and risk consulting. Work with diverse teams to pinpoint challenges in the industry and devise innovative solutions using these technologies. Examine intricate data sets to offer insights that aid in the strategic More ❯