Data Science and AI Technical Product Owner for Pfizer developing analytic and AI systems. Collaborating with leaders in a fast-paced, innovative environment to drive impactful solutions.
Responsibilities
Partner with other leaders to define team roadmap and drive impact by providing strategic and technical input including platform evolution, vendor scan, and new capability development
Communicate value delivered through industrialized AI/ML assets to end user functions (e.g., Chief Marketing Office, PBG Commercial and Medical Affairs) and partner to ideate, design, and implement industrialized assets that can be scaled across markets, brands, and TAs
Partner with Commercial Data team to integrate industrialized assets into enterprise-level analytics data products where appropriate
Partner with Platforms team on continuous development and end to end capability integration between OOB platforms and internal engineered components (API registry, ML library / workflow management, enterprise connectors, AI reusable components); Performance and resource optimization of managed pipelines and models
Lead the advancement of at scale “industrialized” AI and data science capabilities and industrialized asset products
Own vision and maintain a holistic and consistent roadmap for data science and AI products, including data science workflows, AI based software solutions, and AI components
Provide the voice of the user as the product owner on agile product development teams to maximize value and impact of industrialized data science and AI products
Drive adoption of products through user community engagement (e.g., roadshows, training sessions, knowledge sharing etc.)
Develop and maintain business-facing assets documentation/communication for data science and AI products (e.g., value proposition, catalog, and adoption metrics)
Define, monitor, and achieve product success and value metrics
Coordinate with other product and digital teams to ensure data science and AI products fully enable and are integrated into the Commercial data science, analytics and AI ecosystem
Requirements
Bachelor’s degree in analytics related area (Data Science, Computer Engineering, Computer Science, Information Systems, Engineering, or a related discipline)
7+ years of work experience in data science, analytics, engineering, or product management for a diverse range of projects
2-3 years of hands-on product management experience
2+ years of hands-on software development experience, preferably in a cloud environment such as AWS
Track record of managing cross-functional stakeholder groups and effecting change
Clearly articulates expectations, capabilities, and action plans; actively listens with others’ frame of reference in mind; appropriately shares information with team; favorably influences people without direct authority
Clearly articulates scope and deliverables of projects; breaks complex initiatives into detailed component parts and sequences actions appropriately; develops action plans and monitors progress independently; designs success criteria and uses them to track outcomes; drives implementation of recommendations when appropriate, engages with stakeholders throughout to ensure buy-in
Manages projects with and through others; shares responsibility and credit; develops self and others through teamwork; comfortable providing guidance and sharing expertise with others to help them develop their skills and perform at their best; helps others take appropriate risks; communicates frequently with team members earning respect and trust of the team
Experience in translating business priorities and vision into product/platform thinking, set clear directives to a group of team members with diverse skillsets, while providing functional & technical guidance and SME support
Demonstrated experience interfacing with internal and external teams to develop innovative data science solutions
Strong business analysis, product design, and product management skills
Deep expertise with data science enabling technology, such as Dataiku Data Science Studio, AWS SageMaker, Azure AI Foundry or other data science and AI platforms
Strong hands-on skills in analytics engineering and data science (e.g., Python, R, SQL, industrialized ETL software)
Experience working with various types of data (structured / unstructured)
Deep understanding of MLOps principles and tech stack (e.g. MLFlow)
Highly self-motivated to deliver both independently and with strong team collaboration
Ability to creatively take on new challenges and work outside comfort zone
Strong English communication skills (written & verbal)
Benefits
Professional development opportunities
Health insurance
Job title
Senior Manager, Data Science and AI Technical Product Owner
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