Data Engineer at Causalis - Student position
Causalis is a VC-backed startup partnering with the world’s leading pharma companies, building machine learning solutions to bring causal intelligence to healthcare. We are developing a platform of solutions based on novel and proprietary causal AI techniques, to help doctors, patients, and researchers understand and act on the cause-effect relationships in medical data. We are a multi-disciplinary, international team of experts in AI and ML, causal inference and data science, healthcare and medicine. We are looking for smart, driven and overall extraordinary individuals who are passionate about changing the world of personalized medicine, and eager to shape the future of Causalis.
Please contact us with CV/resume at hello@causalis.ai.
Data Engineer - Student position
We're looking for a Data Engineer to work on data and ML pipelines. Causalis is a data based company. As such, all our research and development begin from the accurate treatment of medical data sources and their translation into actionable features and models.
How you’ll contribute:
- Design ETL data models that allow easy storage and retrieval of complex data types from multiple data sources
- Collaborate with epidemiologists and clinicians to identify and define medical entities and features in large multimodal data sets.
- Develop logging, metrics, and alerts that enable us to ensure the data pipelines are up to date and functioning
- Architect and develop health data processing systems for ingestion, integration, storage, and consumption for internal and external users (and at multiple scales)
- Work with data scientists and ML engineers to help build efficient workflows for experimenting with many varied datasets
Our ideal candidate will bring:
- Experience working with backend systems and platforms
- Experience writing production-level code in Java/Spring
- Passionate about TDD and BDD
- Experience with SQL and NoSQL databases and queries, and designing data schemas
- Excellent communication skills and ability to work with technical and non-technical partners
Nice to have:
- Knowledge health/medical data pipelines (including protocols HIPAA, FHIR, etc.)
- Experience in the early-stage startup environment
- Experience developing CI/CD pipelines, and MLOps infrastructure
- Background knowledge of data science
- Familiarity with Docker and Kubernetes