The OmniSeq Knowledgebase Engineer is part of a dynamic, cross-functional team that designs systems and processes to deliver clinically meaningful molecular profiling information and services to oncologists. The Knowledgebase Engineer is a key technical lead in developing/maintaining tools that computationally ingest scientific content for annotation and curation, and subsequent incorporation into laboratory information systems for clinical reporting, clinical evidence analysis, and R&D. This requires working closely across all departments to implement world-class informatics solutions for molecular oncology clinical decision support.
- Develop, document, and manage content retrieval, filtering, parsing and surfacing solutions for public and proprietary scientific content sources.
- Participate in developing and maintaining a database curation tools that allows annotation processes, including automated selection of corpora (drug labels, practice guidelines, and publications), biomedical entity-recognition and disambiguation, and the automated detection of entity relationships.
- Collaborate on development of engine rules to process, validate and integrate scientific and clinical content into laboratory information system (LIS).
- Participate in various analytic activities, including developing programmatic solutions for complex data requests.
- Serve as the main point of contact with external data resources for technical questions/issues.
- Assimilate complex technical concepts and be capable of effectively communicating those concepts to audiences of varying levels of expertise.
- Be proficient at working either independently or within a small team environment on multiple concurrent projects.
- Degree in Biological or Physical Sciences, Computer Science, Mathematics, or Bioinformatics.
- Python development experience.
- Advanced degree in Biological or Physical Sciences.
- Experience in an oncology-related field.
- Engineering content retrieval, parsing, and RDBMS (MySQL) or NoSQL (MongoDB) solutions.
- Experience developing database queries.
- Data mining and natural language processing (NLP) concepts.
- Biomedical vocabularies relevant to cancer, molecular biology and drug discovery.
- Developing clinical grade production software systems.
To apply, please forward your resume to email@example.com