Project Manager, Data Workflow

The American Heart Association is a leading organization focused on combating cardiovascular disease and improving health outcomes. They are seeking a Project Manager for their Multi-Omics Data & Research Operations to oversee and enhance the quality and usability of multi-omics datasets, facilitating collaboration among various stakeholders to deliver impactful data products. This role includes responsibilities such as managing data quality control, developing translation-facing tools, and ensuring compliance with data integrity standards.

Responsibilities:

• Lead and coordinate omics QC/QA across mass spectrometry and elemental platforms, including review of batch effects, missingness, drift, internal standards/QC samples, normalization alignment, outliers, and sample identity tracking
• Develop and/or coordinate standalone applications and interactive dashboards that translate complex multi-omics outputs into accessible insights for research teams, including QC dashboards, cohort/sample exploration, feature and pathway summaries, and reproducible reporting
• Implement pipelines for data documentation, including metadata schemas, processing logs, QC reports, data dictionaries, provenance tracking, dataset versioning, and troubleshooting/interpretation guides, ensuring that multi-omics datasets are discoverable, interpretable, reproducible, and usable by both technical and non-technical stakeholders
• Own timelines, milestones, resourcing, dependency tracking, and risk management across multi-stakeholder omics projects, ensuring clear scientific and technical handoffs and predictable delivery
• Collaborate with data scientists and statisticians to understand requirements and streamline data workflows for advanced analytics. Support querying of real-world multi-omics data related to human subject research and other registries to address high-impact research questions
• Ensure data integrity, access control, and secure handling of sensitive data, aligning operations with IRB requirements and applicable healthcare data regulations and organizational governance policies
• Stay updated on emerging technologies in data engineering, analytics, and data governance; evaluate tools and techniques and propose innovations that enhance data systems, process reliability, and governance practices

Requirements:

• 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
• 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
• Demonstrated 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