Product Owner for In Silico Translational Medicine
Scorpion Therapeutics, Cambridge, Massachusetts, us, 02140
Role Summary
Product Owner for In Silico Translational Medicine focused on leading the creation of AI/ML models for quantitative pharmacology and preclinical safety, and industrializing pilot models and interoperable data solutions. Responsible for ensuring scalability, ease of use, and alignment with Digital standards. Reports to the In Silico Translational Medicine Product Line Owner. Responsibilities
Build partnerships with scientists on the Quantitative Pharmacology and Preclinical Safety teams. Understand the data, in silico models, and analysis platforms they use today to carry out their function within R&D. Identify pain points and opportunities for AI/ML models and interoperable data solutions to advance the R&D pipeline. Collaborate with the Product Line Owner and scientists to write business cases for new product development, prioritizing maximum R&D pipeline acceleration and higher probability of success for therapeutic candidates. Define user stories and product requirements. Prepare work for data scientists and engineers following agile product development best practices. Own and prioritize features on the product roadmap based on scientific impact, business value, and technical feasibility. Facilitate sprint planning with a scrum master. Manage the product backlog. Spearhead user adoption of new products. Outreach to scientists to inform them of new capabilities and provide training materials. Define KPIs and success metrics. Track and report on KPIs to evaluate value provided to the business. Track spend throughout product delivery, ensuring scope stays within budget. Oversee lifecycle management for a portfolio of existing digital solutions used by the Quantitative Pharmacology and/or Preclinical Safety teams, staying aligned with scientists on value and new options in the marketplace. Qualifications
(Required) 5+ years of experience in product management, defining new products and features that provide value to users. Experience translating business requirements to technical specifications. (Required) Proven track record of collaborating with data scientists and/or developers to create products which serve the needs of scientists modeling, analyzing, and/or processing data to advance biomedical research or drug development. (Required) +2 years of experience in the life sciences, preferably in the biopharma sector. (Required) +2 years of experience managing budgets. (Required) Bachelor’s; (Preferred) MS or PhD in Pharmacology, Chemistry, or the Life Sciences (Computational Biology, Bioinformatics, Biochemistry, Molecular Biology, or related field). Skills
Excellent communication skills with a wide range of collaborators and stakeholders. Strong leadership with the ability to command a room and be an empathetic listener. Ability to balance competing priorities with urgency and make data-driven decisions about feature priorities. Curiosity about emerging technologies in AI/ML and scientific computing. Education
(Required) Bachelor’s; (Preferred) MS or PhD in Pharmacology, Chemistry, or the Life Sciences (Computational Biology, Bioinformatics, Biochemistry, Molecular Biology, or related field).
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Product Owner for In Silico Translational Medicine focused on leading the creation of AI/ML models for quantitative pharmacology and preclinical safety, and industrializing pilot models and interoperable data solutions. Responsible for ensuring scalability, ease of use, and alignment with Digital standards. Reports to the In Silico Translational Medicine Product Line Owner. Responsibilities
Build partnerships with scientists on the Quantitative Pharmacology and Preclinical Safety teams. Understand the data, in silico models, and analysis platforms they use today to carry out their function within R&D. Identify pain points and opportunities for AI/ML models and interoperable data solutions to advance the R&D pipeline. Collaborate with the Product Line Owner and scientists to write business cases for new product development, prioritizing maximum R&D pipeline acceleration and higher probability of success for therapeutic candidates. Define user stories and product requirements. Prepare work for data scientists and engineers following agile product development best practices. Own and prioritize features on the product roadmap based on scientific impact, business value, and technical feasibility. Facilitate sprint planning with a scrum master. Manage the product backlog. Spearhead user adoption of new products. Outreach to scientists to inform them of new capabilities and provide training materials. Define KPIs and success metrics. Track and report on KPIs to evaluate value provided to the business. Track spend throughout product delivery, ensuring scope stays within budget. Oversee lifecycle management for a portfolio of existing digital solutions used by the Quantitative Pharmacology and/or Preclinical Safety teams, staying aligned with scientists on value and new options in the marketplace. Qualifications
(Required) 5+ years of experience in product management, defining new products and features that provide value to users. Experience translating business requirements to technical specifications. (Required) Proven track record of collaborating with data scientists and/or developers to create products which serve the needs of scientists modeling, analyzing, and/or processing data to advance biomedical research or drug development. (Required) +2 years of experience in the life sciences, preferably in the biopharma sector. (Required) +2 years of experience managing budgets. (Required) Bachelor’s; (Preferred) MS or PhD in Pharmacology, Chemistry, or the Life Sciences (Computational Biology, Bioinformatics, Biochemistry, Molecular Biology, or related field). Skills
Excellent communication skills with a wide range of collaborators and stakeholders. Strong leadership with the ability to command a room and be an empathetic listener. Ability to balance competing priorities with urgency and make data-driven decisions about feature priorities. Curiosity about emerging technologies in AI/ML and scientific computing. Education
(Required) Bachelor’s; (Preferred) MS or PhD in Pharmacology, Chemistry, or the Life Sciences (Computational Biology, Bioinformatics, Biochemistry, Molecular Biology, or related field).
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