Eagle Genomics is a pioneering company working at the intersection of two exciting areas; life sciences and data science.
If you’re passionate about data,ML/AI, experiments,prototype development, and innovations,join the team and help us change what it means to do real science and drive innovation
On behalf of Eagle Genomics, GT is looking for Data Modeller to join their newly created R&D in Kyiv.
Eagle Genomics is a pioneering company working at the intersection of two exciting areas; life sciences and data science. The exploration into the microbiome is inspiring a new view of biology. Breakthrough research into how microbes interact with humans, animals, and natural ecosystems is creating a wealth of vital data and insight into health, wellbeing, and environmental sustainability. Eagle Genomics operates at the intersection of biology, technology, and data to deliver microbiome discoveries that profoundly change the understanding of wellness and even fundamental assumptions about life on Earth. Their Network Science platform, the e[datascientist], drives novel microbiome insights in ever more accessible, intelligent and relevant ways. Through the blend of scientific expertise, advanced AI, and a genuinely curious and free-thinking culture Eagle Genomics empowers breakthrough possibilities in the true life-changing areas of study.
This is the intersection of ideas, innovation, and intelligence. If you're passionate about data, ML/AI, experiments, prototype development, and innovations, join the team and help us change what it means to do real science and drive innovations.
The Data Modeller plays a critical role in defining and mapping the as is and to be data landscape for our product and will be responsible for maintaining and adjusting the models as new requirements and needs emerge.
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 modeling 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 modeling disciplines (dictionaries, taxonomies, and ontologies). Working knowledge of graph databases, UML, and semantic web technologies would also be helpful
As well as excellent modelling, mapping, and design skills the Data modeler will also play a critical role in governance ensuring that the key stakeholders across the organization ranging from technical engineers to non-technical business folks and scientists have an understanding of the critical concepts of our data model and adhere to the key design principles during the product engineering and build phases.
- Work closely with subject matter experts, data scientists, and product management to gather and translate business needs into the data model(s) that support the platform.
- Evaluating potential data sources to determine how best they can be translated and integrated into our data model. These data sources will be varied - they could be client data, publicly available scientific data or data generated from within Eagle. A thorough assessment of these new data sources will be key to defining and adjusting our data models to accommodate them
- Design, develop and maintain suitable data models, leveraging a variety of modeling techniques defining and documenting the necessary dictionaries, taxonomies, and ontologies that can manage effectively all data platforms (relational, dimensional, NoSQL, and graph) and data tools (reporting, visualization, analytics, and machine learning).
- Troubleshooting and optimizing data systems to ensure that they are aligned effectively to the data models enabling efficient, consistent, and accurate use of data
- Partner closely with the data architect to ensure that the data architecture, data infrastructure, and data interfaces to data sources, tools supporting automated data onboarding, data curation, and metadata management are appropriately defined aligned to the relevant data models.
-Using their strong interpersonal skills the data modeler will work with the relevant leadership to establish and run pragmatic communication, governance, and change management processes and design standards to ensure that the integrity of our designs is maintained.
- Work proactively and independently to address project/product requirements and articulate issues/challenges to reduce project/product delivery risks relating to data models
- Skilled in the development of data models (3NF and graph), dictionaries, taxonomies, and ontologies.
- A strong understanding of data ecosystems
- Experience with master data management and data warehousing architectures and associated data modeling approaches.
- Experience in meta modeling and building dynamic models
- Working knowledge of graph databases, UML, and semantic web technologies
- Excellent interpersonal, communication, and influencing skills
- Experience in building and running pragmatic and effective governance processes
- The candidate must be able to work independently and collaboratively.
GT was founded in 2017 by a former executive from Apple, Nest, and Google. GT’s mission is to build teams and products that address some of the more challenging requirements from fast-growth clients in Europe and North America.
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Job posted on
8 April 2021