Data Modeller - Remote
Eagle Genomics Ltd, United States
Job Description
These are exciting times at Eagle Genomics. We’re at the centre of the digital reinvention of life sciences Ramp;D, using the latest technologies to enable data-driven discovery. As we plan for ambitious, accelerated growth, we have expanded our network of offices in technology and innovation hubs around the world: in the UK, Germany, India, the US and France. So the stage is set to make great steps forward.
Underpinning all of our ambition is a uniquely powerful data-discovery and knowledge-sharing platform that is revolutionising how scientists gain new insight. Now, as we’re about to launch a number of exciting new projects, we’re looking for a Data Modeller to join the team. By using our platform to bridge the gap between data and insight, you will empower biologists to make breakthrough discoveries faster and more efficiently and making a positive impact on the future of society and public health.
We have offices in the Wellcome Genome Centre in Cambridge, WeWorks in London’s Knowledge Quarter, the New York Genome Centre in Manhattan, Station F in Paris and Hyderabad in India. This role is fully remote.
Our goal is to be a knowledge hub for the scientific community, drawing in data from different sources to underpin our innovative e[DataScientist] platform. You will build out and maintain the data model and data model architecture, designing, implementing and documenting solutions that incorporate data curation, machine learning, data science and other capabilities. It is an opportunity to be an advocate of new approaches to modelling, to challenge traditional methods and to embrace constant innovation and iteration.
Requirements
Intellectual curiosity is vital. You will work closely with the business, liaising with non-technical stakeholders to understand requirements, develop new data strategies and identify issues. The expertise to identify architecture, infrastructure and interfaces, define modelling standards, and communicate best practices is essential. You need to be able to work fluidly across a wide range of data platforms (relational, dimensional, NoSQL and graph), data tools (reporting, visualization, analytics, and machine learning) and data modelling disciplines (dictionaries, taxonomies and ontologies). A working knowledge of graph databases, UML and semantic web technologies is also important.
Benefits
- 401k
- 15 days annual leave
- Life cover
- Vision
- Dental
- Medical