Scientific Product Manager
7 hours ago
Lleida
About Xebia With over 20 years of experience, our global network of passionate technologists and pioneering craftsmen deliver cutting-edge technology and game-changing consulting to companies on the brink of transformation. Since 2001, we have grown from a Java company into a full-service digital consulting company with 4500+ professionals working on a worldwide ambition. We are organized in complementary chapters – teams with a tremendous amount of knowledge and experience within a particular field, such as Agile, DevOps, Data and AI, Cloud, Software Technology, Functional Programming, Low Code, and Microsoft. We help the world’s top 250 companies and category leaders overcome digital challenges, embrace innovation, adopt new technology, and implement new business models. In addition to high-quality consulting, we also provide offshoring and nearshoring services. For more details please visit Role Summary The Scientific Product Manager (SPM) owns the strategy, roadmap, and delivery of scientific workspace products across multiple domains. You will identify the highest-value scientific use cases, define product requirements, align cross-functional teams, and drive successful adoption and measurable outcomes for scientists. Key Responsibilities • Own product vision and multi-quarter roadmap across a portfolio of scientific use cases and personas, • Define prioritization frameworks to balance scientific impact, feasibility, time to value, and platform scalability, • Partner with leadership and stakeholders to align product direction with business goals and customer success metrics, • Track competitive landscape and market trends; propose roadmap trade-offs between parity and differentiated innovation, • Develop deep understanding of end-to-end scientific workflows and identify implementation-ready use cases with the highest impact, • Expand the pipeline of new use cases through direct engagement with scientists and teams across functions and modalities, • Standardize how use cases are defined, scoped, and evaluated (problem statement, target user, workflow fit, success metrics, risks, dependencies), • Ensure use cases can be delivered as reusable platform patterns rather than one-off solutions where possible, • Translate scientific needs into clear, testable product requirements for engineering and design (epics, user stories, acceptance criteria), • Lead discovery to delivery execution with engineering, design, data science, and scientific stakeholders in an Agile environment, • Drive dependency management, trade-off decisions, and release planning across multiple concurrent initiatives, • Partner with engineering on validation and testing strategies for deployments in customer environments, including workflow realism and data constraints, • Define go-to-market readiness with stakeholders: documentation, training needs, enablement, and rollout strategy, • Post-launch, measure adoption and outcomes; iterate to improve usability, performance, and scientific value delivered, • Ensure product delivery against challenging scientific goals by maintaining tight feedback loops with end users and adjusting roadmap as needed Basic Qualifications • Bachelor’s or Master’s degree in bioinformatics, biology, or a related scientific discipline plus at least 5 years of relevant experience (PhD preferred), • Product management experience shipping software products, ideally across complex workflows and multiple user personas, • Ability to translate ambiguous scientific problems into structured product plans and engineering-ready requirements Preferred Qualifications • Experience in pharma, biotech, and or digital health environments, • Strong analytical and critical thinking skills; ability to synthesize complex inputs into clear decisions and narratives, • Working knowledge of data analysis and experimentation; Python, R, or MATLAB beneficial, • Excellent communication and collaboration skills in cross-functional, global teams, • Experience working in Agile or Scrum environments, • Foundation in biology across discovery concepts such as target discovery, NGS, small molecule discovery, and large molecule discovery
Carrer Enric Pubill "Lo Parrano", 25005, Lleida
