Project Manager

Key responsibilities include:

• End-to-end project management for data science and analytics initiatives
  

• Coordination between technical and business stakeholders
  

• Tracking project progress, risks, and outcomes using agile or hybrid methodologies
  

• Supporting the ope rationalization of AI models and data products
  

• Managing communications, documentation, and governance workflows
  

• Develop and maintain project documentation including project plans, technical specifications, sprint boards, meeting agendas, and reports.
  

• Coordinate timelines, dependencies, and deliverables for multiple concurrent data science and AI projects.
  

• Partner with data scientists to translate technical findings into actionable insights for business and clinical teams.
  

• Facilitate meetings and cross-functional collaboration to ensure alignment between data, technology, and operations.
  

• Track metrics such as model performance, deployment timelines, and business impact post-implementation.
  

• Support the creation of dashboards, project trackers, and communication artifacts to enhance transparency and accountability.
  

• Conduct readiness assessments and manage implementation plans for AI and analytics pilots.
  

• Manage intake and prioritization processes for new data science project requests.
  

• Document workflows, data pipelines, and governance processes for reproducibility and compliance.
  

• Support vendor evaluations and partnerships for data platforms, analytics tools, or AI solution o
  

• Requirements:
  

  • Bachelor's Degree in Data Science Analytics, Computer Science, Engineering, or related field. 1-3 years of experience in project management, preferably supporting analytics or data science initiatives.
    

  • Familiarity with data science workflows, tools (e.g., Python, SQL, Power BI, Snowflake, Azure ML, Data-bricks), and lifecycle management.
    

  • Experience working in healthcare, life sciences, or research environments preferred.
    

  • Ability to communicate effectively with both technical and non-technical stakeholders.
    

  • Strong organizational and documentation skills; ability to manage multiple work streams simultaneously.
    

  • Experience translating complex data concepts into business outcomes.
    

  • Knowledge of data governance, security, and compliance (HIPAA preferred).
    

  • Proficiency in Microsoft Office Suite, Azure DevOps or similar tools.