MSD
Overview
We are seeking an experienced Technical Product Manager to lead pharmaceutical process and method development data product portfolio. This role combines a strong understanding of biopharma research, hands-on experience with pharmaceutical process and method development, tech transfer for commercial manufacturing, and the ability to drive product strategy and execution. The successful candidate will be accountable for timely availability of quality, reliable data to support insights needs for scientific and operational decisions that aid innovation and productivity. Key Responsibilities
Collaborate with stakeholders to understand their business data needs for in silico research, and define the core capabilities required to support these needs.
Develop and communicate a product vision, strategy, and roadmap for pharmaceutical process and method development data products that align with business objectives and market opportunities.
Act as the primary point of contact for stakeholders regarding product vision, strategy, and roadmap updates.
Apply Agile methodologies in managing the product development lifecycle, including sprint planning, backlog management, and performance assessments.
Apply prototyping techniques to learn and evolve the product.
Create and lead cross-functional teams comprising data scientists, information architects, software engineers, and product designers to drive product development and execution.
Conduct regular meetings with stakeholders and product team members to provide updates and motivate the team to achieve execution goals.
Ensure the product team is aligned with the overall product vision and motivated to contribute to successful execution.
Leverage hands-on experience with data to inform product features.
Support the development of tools and methodologies that facilitate processing and analysis of process and analytical data.
Foster a collaborative environment that encourages open communication and aligns team efforts with the product roadmap.
Advocate for the adoption of FAIR (Findable, Accessible, Interoperable, Reusable) data principles in the development of pharmaceutical process and method development data products.
Highlight the need for, and assist stakeholders with, data capture, master data standards, and documentation practices to ensure data findability and accessibility.
Enable automation and monitoring solutions that enhance workflow efficiency and data integrity.
Ensure compliance with GxP and audit requirements for data usage and dashboarding.
Be accountable for execution and delivery timelines related to pharmaceutical process and method development data products.
Drive adoption of delivered data products through user training, documentation, pilots, and evangelism; collect feedback and iterate.
Measure and report on adoption metrics and business outcomes (e.g., reduced cycle time, fewer deviations, improved batch yield).
Qualifications
Bachelor’s degree in Life Sciences, Biomedical Engineering, Chemical Engineering, Computer Science, or a related field; advanced degree preferred.
5+ years of experience in technical product management, particularly within the biopharma or healthcare sectors.
Demonstrated understanding of Physicochemical data, process data, stability and other analytical data.
Experience with cloud storage and compute infrastructure (e.g., AWS, Azure) and knowledge of automation and monitoring tools.
Familiarity with FAIR data principles and best practices related to data management and interoperability.
Strong experience with Agile methodologies and product management frameworks.
Excellent leadership, communication, and stakeholder management skills.
Ability to simplify complex technical and scientific concepts for nontechnical stakeholders.
Proven ability to prioritize competing demands and drive cross-functional teams.
Proven ability to motivate cross-functional teams and drive product strategy from conception to execution.
Familiarity with systems like Signals, PKM, Pi, Databricks, Redshift, and modern data architecture tools.
Strong understanding of data modeling, governance, and analytics platforms (e.g., Power BI, Collibra).
Knowledge of GxP compliance and regulatory data standards.
Preferred Qualifications
Prior experience in a pharma/biotech organization’s process development, manufacturing, or automation team.
Hands-on experience with tools such as LIMS (e.g., Labware), ELN (e.g., Benchling), MES, SCADA, OSIsoft PI, Apache Kafka, Spark, Databricks, or similar.
Experience participating in tech transfer projects, method validations, or PAT-enabled implementations.
Familiarity with AI/ML use cases in bioprocessing (digital twins, predictive control, anomaly detection).
Demonstrated experience translating process/experimental requirements into data/IT solutions and shipping data products in regulated environments.
End of description.
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We are seeking an experienced Technical Product Manager to lead pharmaceutical process and method development data product portfolio. This role combines a strong understanding of biopharma research, hands-on experience with pharmaceutical process and method development, tech transfer for commercial manufacturing, and the ability to drive product strategy and execution. The successful candidate will be accountable for timely availability of quality, reliable data to support insights needs for scientific and operational decisions that aid innovation and productivity. Key Responsibilities
Collaborate with stakeholders to understand their business data needs for in silico research, and define the core capabilities required to support these needs.
Develop and communicate a product vision, strategy, and roadmap for pharmaceutical process and method development data products that align with business objectives and market opportunities.
Act as the primary point of contact for stakeholders regarding product vision, strategy, and roadmap updates.
Apply Agile methodologies in managing the product development lifecycle, including sprint planning, backlog management, and performance assessments.
Apply prototyping techniques to learn and evolve the product.
Create and lead cross-functional teams comprising data scientists, information architects, software engineers, and product designers to drive product development and execution.
Conduct regular meetings with stakeholders and product team members to provide updates and motivate the team to achieve execution goals.
Ensure the product team is aligned with the overall product vision and motivated to contribute to successful execution.
Leverage hands-on experience with data to inform product features.
Support the development of tools and methodologies that facilitate processing and analysis of process and analytical data.
Foster a collaborative environment that encourages open communication and aligns team efforts with the product roadmap.
Advocate for the adoption of FAIR (Findable, Accessible, Interoperable, Reusable) data principles in the development of pharmaceutical process and method development data products.
Highlight the need for, and assist stakeholders with, data capture, master data standards, and documentation practices to ensure data findability and accessibility.
Enable automation and monitoring solutions that enhance workflow efficiency and data integrity.
Ensure compliance with GxP and audit requirements for data usage and dashboarding.
Be accountable for execution and delivery timelines related to pharmaceutical process and method development data products.
Drive adoption of delivered data products through user training, documentation, pilots, and evangelism; collect feedback and iterate.
Measure and report on adoption metrics and business outcomes (e.g., reduced cycle time, fewer deviations, improved batch yield).
Qualifications
Bachelor’s degree in Life Sciences, Biomedical Engineering, Chemical Engineering, Computer Science, or a related field; advanced degree preferred.
5+ years of experience in technical product management, particularly within the biopharma or healthcare sectors.
Demonstrated understanding of Physicochemical data, process data, stability and other analytical data.
Experience with cloud storage and compute infrastructure (e.g., AWS, Azure) and knowledge of automation and monitoring tools.
Familiarity with FAIR data principles and best practices related to data management and interoperability.
Strong experience with Agile methodologies and product management frameworks.
Excellent leadership, communication, and stakeholder management skills.
Ability to simplify complex technical and scientific concepts for nontechnical stakeholders.
Proven ability to prioritize competing demands and drive cross-functional teams.
Proven ability to motivate cross-functional teams and drive product strategy from conception to execution.
Familiarity with systems like Signals, PKM, Pi, Databricks, Redshift, and modern data architecture tools.
Strong understanding of data modeling, governance, and analytics platforms (e.g., Power BI, Collibra).
Knowledge of GxP compliance and regulatory data standards.
Preferred Qualifications
Prior experience in a pharma/biotech organization’s process development, manufacturing, or automation team.
Hands-on experience with tools such as LIMS (e.g., Labware), ELN (e.g., Benchling), MES, SCADA, OSIsoft PI, Apache Kafka, Spark, Databricks, or similar.
Experience participating in tech transfer projects, method validations, or PAT-enabled implementations.
Familiarity with AI/ML use cases in bioprocessing (digital twins, predictive control, anomaly detection).
Demonstrated experience translating process/experimental requirements into data/IT solutions and shipping data products in regulated environments.
End of description.
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