AI/ML Engineer - GTRI-ICL
Tasks
- Analyze longitudinal health trends
- Build data visualizations
- Collaborate with multidisciplinary researchers
- Communicate data findings written and verbal
- Condition process filter fuse data
- Deploy machine learning models
- Design logging and debug using logs
- Develop and apply machine learning and statistical models
- Develop machine learning models
- Ensure data quality manage metadata
- Explore literature to develop solutions
- Integrate multi-source data
- Mentor students and junior data scientists
- Perform statistical analyses
- Research statistical foundations for nonlinear systems
- Review work for quality improvement
- Use linked datasets to study clinical and geospatial factors
Perks/Benefits
Skills/Tech-stack
APIs | CSV | Common Data Model | Computer Vision | Data Filtering | Data Fusion | Data Model | Data Processing | Data Visualization | Data cleaning | Data conditioning | Data environments | Data integration | Databricks | Debugging | Distributed Computing | Genetic Programming | High Performance | High-Performance Computing | LOINC | Language Models | Language Processing | Large Language Models | Logging | Machine Learning | Matplotlib | Natural Language | Natural Language Processing | NumPy | OHDSI | OMOP common data model | Pandas | Parallel Computing | Patient Level Prediction | Performance Computing | Population Level Estimation | PostgreSQL | Power BI | Python | R | Relational databases | SNOMED | SQL | Secure Data | Secure Data Environments | Shiny | Statistics | Tableau | Web Scraping
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI/ML Engineer | Data Scientist | Engineer | ML Engineer | Scientist
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