1. Lead the development of next-generation sequencing (NGS) algorithms for different applications. 2. Transform specialized big data analysis and AI algorithms into reusable pipelines and scalable (distributed) systems. 3. Work as a professional team player with data scientists, AI specialists and IT/platform architects to implement auto-pipelines/frameworks of big data genomics analytics. 4. Build and deploy visual/interactive analytics interfaces/frameworks with data scientists. 5. Convert requirements in domain languages into executable technical specifications. 6. Troubleshoot and maintain big data analytics pipeline, training for internal customers.
1. Bachelor or above in STEM or related areas (computer science, data science, machine learning, information systems or engineering) with preferably industrial experience in data engineering. 2. Knowledge in data analysis, machine learning with proficiency in one or more programming languages (Python, Java, Scala, R, SQL, NoSQL), familiarity with front-end (D3, AngularJS, Node.js) and MVC frameworks. 3. Solid knowledge in data structures and data analysis, machine learning methods. 4. Good sense of domain languages with good communication to understand and translate business needs into technical specifications. 5. Passion in AI technology, motivations on challenging real-world problems, and excellent teamwork. 6. Familiarity with bioinformatics, genomics and oncology.