About XebiaWith 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 SummaryThe 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.
Sea uno de los primeros solicitantes, lea la descripción completa del puesto a continuación y luego envíe su candidatura para que sea considerada.
Key ResponsibilitiesOwn product vision and multi-quarter roadmap across a portfolio of scientific use cases and personasDefine prioritization frameworks to balance scientific impact, feasibility, time to value, and platform scalabilityPartner with leadership and stakeholders to align product direction with business goals and customer success metricsTrack competitive landscape and market trends; propose roadmap trade-offs between parity and differentiated innovationDevelop deep understanding of end-to-end scientific workflows and identify implementation-ready use cases with the highest impactExpand the pipeline of new use cases through direct engagement with scientists and teams across functions and modalitiesStandardize 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 possibleTranslate 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 environmentDrive dependency management, trade-off decisions, and release planning across multiple concurrent initiativesPartner with engineering on validation and testing strategies for deployments in customer environments, including workflow realism and data constraintsDefine go-to-market readiness with stakeholders: documentation, training needs, enablement, and rollout strategyPost-launch, measure adoption and outcomes; iterate to improve usability, performance, and scientific value deliveredEnsure product delivery against challenging scientific goals by maintaining tight feedback loops with end users and adjusting roadmap as needed
xiphtebBasic QualificationsBachelor'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 personasAbility to translate ambiguous scientific problems into structured product plans and engineering-ready requirements
Preferred QualificationsExperience in pharma, biotech, and or digital health environmentsStrong analytical and critical thinking skills; ability to synthesize complex inputs into clear decisions and narrativesWorking knowledge of data analysis and experimentation; Python, R, or MATLAB beneficialExcellent communication and collaboration skills in cross-functional, global teamsExperience working in Agile or Scrum environmentsFoundation in biology across discovery concepts such as target discovery, NGS, small molecule discovery, and large molecule discovery