The University of Texas MD Anderson Cancer Center
Data Science Project Manager
The University of Texas MD Anderson Cancer Center, Boston, Massachusetts, us, 02298
Job Title:
Data Science Project Manager Job Number:
36958 Location:
Boston, MA Responsibilities
Lead, mentor, and coordinate the AI/ML and software development teams in Boston. Own sprint planning, task assignment, and technical delivery milestones. Review and contribute to code (Python, R, or equivalent). Oversee data architecture, model deployment, and API integration across internal stack. Validate all scientific data pipelines, ensuring biological accuracy and integrity. Bridge communication between engineering and bioinformatics to align outputs with research and clinical logic. Evaluate ML models for biological relevance, bias, and reproducibility. Collaborate with leadership to align development progress with strategic scientific goals. Required Skills
Bachelor’s or Master’s in Bioinformatics, Computational Biology, or Computer Science (or equivalent). Strong coding ability in Python (and ideally R or SQL). Deep understanding of multi-omics data, biological validation, and scientific workflows. Experience managing cross-disciplinary technical teams. Familiarity with machine-learning pipelines, data integration, and scientific reproducibility standards. PMP, Scrum Master, or similar project management certification is a plus. Preferred
PhD in a computational or biological discipline. Experience with digital twin, precision-medicine, or health-AI projects. Knowledge of cloud infrastructure (AWS, GCP) and containerization (Docker/Kubernetes). Comfort with biomedical data standards (FHIR, HL7, OMOP).
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Data Science Project Manager Job Number:
36958 Location:
Boston, MA Responsibilities
Lead, mentor, and coordinate the AI/ML and software development teams in Boston. Own sprint planning, task assignment, and technical delivery milestones. Review and contribute to code (Python, R, or equivalent). Oversee data architecture, model deployment, and API integration across internal stack. Validate all scientific data pipelines, ensuring biological accuracy and integrity. Bridge communication between engineering and bioinformatics to align outputs with research and clinical logic. Evaluate ML models for biological relevance, bias, and reproducibility. Collaborate with leadership to align development progress with strategic scientific goals. Required Skills
Bachelor’s or Master’s in Bioinformatics, Computational Biology, or Computer Science (or equivalent). Strong coding ability in Python (and ideally R or SQL). Deep understanding of multi-omics data, biological validation, and scientific workflows. Experience managing cross-disciplinary technical teams. Familiarity with machine-learning pipelines, data integration, and scientific reproducibility standards. PMP, Scrum Master, or similar project management certification is a plus. Preferred
PhD in a computational or biological discipline. Experience with digital twin, precision-medicine, or health-AI projects. Knowledge of cloud infrastructure (AWS, GCP) and containerization (Docker/Kubernetes). Comfort with biomedical data standards (FHIR, HL7, OMOP).
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