Job Description: Pay Range: $195000year $218000year
- Master's Degree in related field highly preferred OR relevant bachelor's degree plus 5 additional years of related experience.
- Minimum of 5 years of experience in leading and managing data and analytics teams with at least 3 years managing data science and AI projects or teams in a research or healthcare setting.
- Experience in mentoring and supervising data scientists, machine learning engineers, and product/data analysts.
- Experience managing successful collaborations with faculty, CROs, administrators, clinical leaders, and other external organizations.
- Demonstrated expertise in applying advanced statistical and machine learning techniques to real-world problems, such as predictive modeling, natural language processing, computer vision, or recommender systems at scale.
- Demonstrated expertise in managing the entire AI/ML lifecycle, from ideation, data acquisition and model training, to production deployment and monitoring, including developing scalable AI/ML CI/CD solutions.
- Strong communication and presentation skills, with the ability to explain complex technical concepts to diverse audiences, such as clinicians, researchers, administrators, or faculty.
- bility to interact and communicate effectively with senior executive teams.
- Demonstrated ability to lead and influence experienced professionals.
- bility to think critically, creatively, and to anticipate and solve problems.
- bility to navigate and be successful in a fast-paced, highly-matrixed work environment.
- Experience in securing and managing grants and contracts for data science and AI initiatives, as well as adhering to ethical and regulatory standards for data privacy and security preferred.
- Proficient in using various programming languages and tools for data analysis and machine learning, such as AWS Sagemaker, Comprehend Medical, Python, SQL, Tensor Flow, PyTorch, or Spark preferred.
ccountabilities:
- Define and own the standard of excellence for data science, machine learning, and AI.
- Lead the data science and AI team to design, develop, and implement innovative solutions that leverage data and advanced analytics to improve health outcomes, quality of care, and operational efficiency.
- Collaborate and establish partnerships with clinical, research, and administrative stakeholders to represent team capabilities/aspirations and identify high-impact use cases.
- Manage the end-to-end lifecycle of data and AI projects, including data acquisition, preprocessing, modeling, validation, deployment, monitoring, and maintenance.
- Provide technical guidance and mentorship to data scientists, engineers, and product/data analysts on the best practices and standards of data and AI development and delivery.
- Operate within the data and AI governance framework to ensure ethical, legal, and responsible use of data and AI across the organization.
- Promote a culture of continuous learning and adapting by evaluating and adopting new emerging technologies, tools, and methodologies that enhance the data and AI capabilities and performance of the team and the organization.
- pply a detailed understanding of data science and translational medicine to ensure of Client's is at the cutting edge of both current and future applications.
- Establish repeatable processes, playbooks, standards, and best practices to ensure the team is identifying and delivering cumulative value with zero technical debt and to drive adoption, consistency, and scale across teams.
- Communicate and disseminate data and AI insights and results to various audiences, including senior leadership, clinicians, researchers, and external partners.
- Drive a culture of innovation and continuous improvement, ensuring the team is driving a mindset to creatively and collaboratively challenge and improve established best practice standards.
- Provide strategic guidance to Data, Analytics, and AI Executive Leadership in addition to other senior leaders.