Project Manager, Data Workflow

Overview

Since our founding in 1924, we've cut cardiovascular disease deaths in half, but there is still so much more to do. To overcome today’s biggest health challenges and accelerate this progress, we need passionate individuals like you. Join our movement, be part of the progress, and help ensure a healthier future for all. You matter, and so does the impact you can make with us.

The American Heart Association has an excellent opportunity for a Project Manager, Multi-Omics Data & Research Operations
, working with the Periodic Table of Food Initiative (PTFI)®. This position can be home‑based and is full‑time, benefits‑eligible, grant‑funded. Current funding will expire on March 1, 2027, but may be extended. The PTFI® is a science‑to‑action initiative co‑managed by the American Heart Association that offers standardized multi‑omics tools, data, and training to characterise food quality of the world’s edible biodiversity.

As the dataset expands, this role will strengthen omics data quality, documentation, and usability across research teams and partners.

• Multi‑Omics Data QC and Readiness:
  Lead and coordinate omics QC/QA across mass spectrometry and elemental platforms (e.g., LC‑MS/MS metabolomics, proteomics, lipidomics; ICP‑MS ionomics; HPLC‑ICP‑MS speciation), including review of batch effects, missingness, drift, internal standards/QC samples, normalization alignment, outliers, and sample identity tracking. Define and maintain criteria for analysis‑ready datasets and cross‑omics linkages (sample to assay to feature matrix to results).
• Translation‑Facing Data Products:
  Develop and/or coordinate standalone applications and interactive dashboards (e.g., R/Shiny or comparable frameworks) 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.
• Data Documentation and Provenance Pipelines:
  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.
• Cross‑Functional Project Management:
  Own timelines, milestones, resourcing, dependency tracking, and risk management across multi‑stakeholder omics projects, ensuring clear scientific and technical handoffs and predictable delivery.
• Analytics Enablement and Data Query Support:
  Collaborate with data scientists and statisticians to understand requirements and streamline data workflows for advanced analytics (e.g., ML‑ready matrices, harmonized covariates/phenotypes, feature annotation and mapping). Support querying of real‑world multi‑omics data related to human subject research and other registries to address high‑impact research questions.
• Data Integrity, Security, and Compliance:
  Ensure data integrity, access control, and secure handling of sensitive data, aligning operations with IRB requirements and applicable healthcare data regulations (e.g., HIPAA where relevant) and organizational governance policies.
• Continuous Improvement and Innovation:
  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.

• 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…