Project Manager, Research and Data Workflow

The American Heart Association is dedicated to improving cardiovascular health and has an opening for a Project Manager, Research and Data Workflow. This role involves coordinating multi-omics research projects, ensuring efficient data workflows, and translating complex datasets into actionable insights.

Responsibilities:

• Coordinate research studies and deliverables across the PTFI ecosystem, including timelines, milestone tracking, data/metadata handoffs, and reporting
• Facilitate research collaboration across laboratories, researchers, and technical teams to ensure efficient project execution
• Support study design and execution in partnership with PIs and laboratories
• Coordinate procurement, tracking, and chain-of-custody of food samples, biospecimens, and associated metadata to ensure analysis-ready datasets
• Ensure datasets meet defined standards for analysis readiness and cross-omics integration
• Coordinate quality control processes across omics platforms (e.g., LC-MS/MS metabolomics, lipidomics, proteomics; ICP-MS ionomics; speciation workflows
• Review and track batch effects, drift, missingness, internal standards/QC samples, normalization alignment, outliers, and sample identity
• Implement documentation and provenance pipelines including metadata schemas, QC reports, processing logs, dataset versioning, and data dictionaries
• Maintain reproducible workflows that ensure datasets are interpretable, discoverable, and usable across research teams
• Support PIs and collaborators with data analysis workflows and interpretation
• Contribute to manuscript preparation, figures, and reproducible supplements; serve as a coauthor when appropriate
• Develop or coordinate interactive dashboards and standalone tools (e.g., R/Shiny or comparable frameworks) that translate complex multi-omics outputs into accessible insights for research teams
• Collaborate with data scientists and statisticians to prepare ML-ready datasets and support advanced analytics
• Contribute to development of AI-enabled tools, indices, and scoring systems that translate multi-omics data into actionable measures of food quality and health relevance
• Monitor emerging tools and best practices in data engineering, analytics, and governance
• Identify opportunities to improve data workflows, system reliability, and research data usability

Requirements:

• MSc or PhD strongly preferred in bioinformatics, computational biology, analytical chemistry, biomedical informatics, horticulture/plant/food sciences, or a related field
• 3+ years of experience supporting multi-omics or high-dimensional datasets in research, clinical, agricultural, or translational settings, with demonstrated project management ownership
• Experience collaborating with partners on study design, sample logistics, and publication development (e.g., coauthoring manuscripts, abstracts, or reports
• Hands-on understanding of omics data QC concepts and assay outputs (e.g., MS-based peak/feature tables, ionomics matrices, speciation workflows), including batch effects, drift, internal standards/QC samples, normalization, missingness, outliers, and sample tracking
• Experience developing reproducible data analysis workflows in R (e.g., scripts, R Markdown/Quarto) and building or partnering to deliver interactive tools for scientific users (e.g., Shiny apps, dashboards, standalone visualization applications
• Knowledge of data integrity, security, and compliance expectations for human-subject or sensitive data (e.g., IRB-aligned workflows; HIPAA familiarity where applicable) and best practices for controlled-access data products
• Strong written and communication skills, including ability to author clear documentation, tutorials, and troubleshooting guides and translate technical concepts for mixed audiences
• Highly organized, detail-oriented, and able to manage multiple priorities in a fast-paced, cross-functional environment; comfort coordinating conferences, working groups, and external partner deliverables
• Ability to travel up to 10% local and overnight stay