Clinical Data Scientist

Meharry Medical College (MMC) is seeking a highly skilled and innovative Clinical Data Scientist to join the Enterprise Data and Analytics (EDA) division. This role will focus on leveraging advanced data science techniques and methodologies to analyze clinical data, support predictive modeling, and develop actionable insights that improve health outcomes and reduce disparities. The Clinical Data Scientist will play a critical role in advancing health equity by working with diverse datasets, applying machine learning, and creating impactful data-driven solutions for underserved populations. Additionally, the Clinical Data Scientist will provide critical support for the Engaging Cooperative Sites for Trial Acceleration, Trust, Innovation, and Capability (ECSTATIC) grant objectives, contributing to collaborative efforts to enhance clinical trial efficiency, improve participant diversity, and ensure equity in clinical research outcomes. This position offers an exciting opportunity to contribute to cutting-edge healthcare initiatives at Meharry Medical College, where you will collaborate across clinical, research, and technical teams to solve complex challenges and deliver transformative results.

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.

---