Clinical Data Scientist
1 week ago
Essential Functions (Duties and Responsibilities) – Assign a percentage to each essential function (equal to 100%):
1. Data Analysis and Management
- Work with large-scale clinical and multimodal datasets to extract insights and improve health outcomes.
- Manage and preprocess clinical data, including cleaning, transforming, and ensuring data integrity.
- Perform data mining, statistical analysis, and modeling to uncover trends and actionable insights.
30%
2. Predictive Modeling and Machine Learning
- Develop and implement machine learning models for clinical predictions, including disease risk assessments and treatment optimizations.
- Leverage multimodal learning frameworks for analyzing imaging, genomic, and structured clinical data.
- Ensure the fairness, equity, and transparency of predictive models to address healthcare disparities.
40%
3. Support ECSTATIC Grant Objectives
- Collaborate with grant stakeholders to support clinical trial acceleration and diversity initiatives.
- Design and analyze datasets to enhance clinical trial efficiency and equity.
- Provide technical expertise and data-driven insights to meet grant deliverables and objectives.
20%
4. Collaboration and Reporting
Collaborate with cross-functional teams, including clinicians, researchers, and IT professionals, to design and execute data-driven projects. Prepare, present, and publish findings in internal meetings, research conferences, and peer-reviewed journals. Create data visualizations and reports for both technical and non-technical audiences.
10%
=100%
Knowledge, Skills and Abilities:
- Proficiency in programming languages such as Python, R, or SQL for data analysis and modeling.
- Expertise in machine learning and deep learning techniques, including neural networks, clustering, and transfer learning.
- Ability to analyze large imaging datasets and knowledge of computer vision.
- Knowledge of statistical methods, including regression, hypothesis testing, and distributions.
- Experience with clinical data standards, such as HL7, FHIR, OMOP, and PCORnet.
- Strong communication skills for engaging with diverse stakeholders and translating complex insights into actionable recommendations.
- Knowledge of data privacy and security frameworks such as HIPAA, and similar regulatory standards.
Education and Experience:
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Biomedical Informatics, or a related field.
- 2+ years of experience in clinical data science, predictive modeling, or biomedical data analysis.
- Familiarity with healthcare systems, clinical workflows, and EHR systems.
- Experience applying AI/ML techniques to real-world healthcare problems.
Environmental Conditions and Physical Demands
- Work is normally performed in a typical interior/office work environment.
- None or very limited physical effort required.
- None or very limited exposure to physical risk.
- May require extended work hours and/or travel.
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