Overview
Remote
Depends on Experience
Full Time
Skills
Data Science
AI
Job Details
Brief Overview The Technical Product Manager of Data Science Products will report to the Data Science Director to lead the development and implementation of innovative data and AI products for our healthcare system. This role requires a unique blend of technical expertise, product vision, and a passion for improving healthcare through data-driven solutions. You will collaborate closely with crossfunctional teams, including data scientists, engineers, clinicians, and researchers, to deliver cuttingedge products that address critical needs within our academic medical center. This role is in a new team supporting Stanford Medicine's inaugural Chief Data Scientist in building Stanford Health Care's (SHC) solutions that incorporate Artificial Intelligence (AI) to improve patient care, medical research, and administrative services. This team was created to bring AI, predictive algorithms and other emerging machine learning (ML) based innovations in data science into healthcare and will partner closely with individuals across clinical specialties and operations areas to deploy algorithms that lead to better patient outcomes.
What you will do:
Define and execute the product vision and roadmap for data and AI products, aligning technical capabilities with the strategic objectives of the medical center.
This involves:
o Collaborating closely with engineering teams to ensure the technical feasibility and scalability of products.
o Prioritizing user needs based on user research, market trends, and SHC business objectives.
o Defining product requirements, user flows, and success metrics
Define and execute the product vision and roadmap for data and AI products, aligning technical capabilities with the strategic objectives of the medical center.
This involves:
o Collaborating closely with engineering teams to ensure the technical feasibility and scalability of products.
o Prioritizing user needs based on user research, market trends, and SHC business objectives.
o Defining product requirements, user flows, and success metrics
Lead the product development lifecycle, including planning, execution, and delivery of new features and products.
This involves:
o Developing and maintaining a product roadmap.
o Managing the product backlog.
o Facilitating sprint planning progress.
o Managing product releases and collecting user feedback.
This involves:
o Developing and maintaining a product roadmap.
o Managing the product backlog.
o Facilitating sprint planning progress.
o Managing product releases and collecting user feedback.
Generate detailed product requirement documents that include different jobs to be done throughout the data lifecycle. This will include thinking through data ingestion, data governance, and data delivery.
Effectively communicate project status, progress, and outcomes to stakeholders.
Drive product adoption and iteration, monitoring product performance, gathering feedback, and identifying opportunities for improvement. Education
Effectively communicate project status, progress, and outcomes to stakeholders.
Drive product adoption and iteration, monitoring product performance, gathering feedback, and identifying opportunities for improvement. Education
Qualifications
Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
Experience Qualifications
5+ years of experience as a technical product or program manager, product owner, solutions architect, or similar role, preferably in a data science or analytics environment.
Strong technical background, including knowledge of data science methodologies, tools, and technologies (e.g., Python, R, SQL, Machine Learning frameworks).
Experience working with cloud platforms (e.g., Azure, Google Cloud Platform, AWS).
General understanding of data engineering concepts
Experience with agile project management methodologies (e.g., Scrum).
5+ years of experience as a technical product or program manager, product owner, solutions architect, or similar role, preferably in a data science or analytics environment.
Strong technical background, including knowledge of data science methodologies, tools, and technologies (e.g., Python, R, SQL, Machine Learning frameworks).
Experience working with cloud platforms (e.g., Azure, Google Cloud Platform, AWS).
General understanding of data engineering concepts
Experience with agile project management methodologies (e.g., Scrum).
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