Senior Product Manager - Small Molecule and Computational Chemistry
hace 9 días
Valencia
About the Role We are looking for a Senior Technical Product Manager to join our life sciences R&D product team, supporting large-scale digital transformation initiatives for a leading pharmaceutical client. This role requires a strong combination of technical depth, product strategy, and stakeholder management, focused on complex platform products used by researchers, scientists, and data engineers across computational chemistry and small molecule drug discovery domains. You will take ownership of strategic products or portfolios of applications, driving continuous discovery, innovation, and measurable business value within a hybrid delivery model that combines agile execution with structured governance frameworks (PDLC). This is a highly collaborative, partnership-driven role where you will work closely with engineering teams, business stakeholders, and multi-vendor environments to deliver impactful R&D solutions. What You’ll Do • Own the end-to-end product lifecycle for R&D platform products, from strategy and roadmap definition to delivery and continuous value validation, • Lead products through structured governance frameworks (e.g., PDLC), ensuring alignment across strategy, requirements, architecture, and launch checkpoints, • Drive product discovery through user research, stakeholder engagement, and continuous feedback loops with scientists and business users, • Translate complex scientific and technical requirements into clear product plans, user stories, and prioritized backlogs, • Collaborate closely with engineering, data, and business teams to define solutions, manage dependencies, and ensure successful delivery, • Drive release planning, UAT, and launch readiness across technical and non-technical stakeholders, • Operate effectively within a hybrid delivery model, balancing agile execution with structured governance requirements, • Leverage AI tools (e.g., Gemini Pro, Atlassian AI) to enhance prioritization, velocity forecasting, and product insights, • Apply data-driven techniques such as sentiment analysis and predictive analytics to inform backlog prioritization and decision-making, • Co-develop AI/GenAI use cases with stakeholders to improve research workflows and product capabilities, • Promote automation in documentation and requirements generation through AI-powered solutions, • Maintain high-quality documentation and communicate progress, risks, and outcomes to stakeholders and governance forums What You Bring • 8+ years of experience in product management, ideally in technical or platform-based environments, • Experience in computational chemistry or small molecule drug discovery workflows, particularly in areas such as molecular modeling, assay data, or compound-related platforms, • Experience working in regulated or complex domains (e.g., life sciences), with the ability to bridge technical and non-technical audiences, • Experience delivering AI-native or data-intensive products, including the application of AI/GenAI capabilities within product environments, is highly valued, • Proven ability to define product strategy, manage roadmaps, and deliver business value in complex environments, • Strong experience translating ambiguous requirements into structured documentation and actionable plans, • Solid understanding of agile methodologies and experience working within hybrid delivery models, • Advanced proficiency with tools such as Jira and Confluence for backlog management and documentation, • Strong technical background, with experience working with cloud platforms (GCP preferred), APIs, and data-driven systems, • Ability to collaborate effectively with engineers, data teams, and business stakeholders Nice to Have • Experience with high-performance computing (HPC) environments or large-scale data processing, • Familiarity with authentication systems (e.g., SSO, LDAP) and enterprise security models, • Experience working in multi-vendor environments, • Knowledge of data movement challenges related to large-scale scientific datasets, • Cloud certifications (e.g., GCP Professional Cloud Architect)
