Senior Specialist, Technical Product Management

Responsibilities Collaborate closely with Product, Data Science, and Engineering teams to define and develop data products tailored for drug discovery and preclinical research. Gather, manage, and prioritize product requirements by engaging with scientific stakeholders to understand user problems, technical constraints, and strategic objectives. Define and refine the product backlog; create actionable user stories that reflect the unique workflows and challenges of preclinical drug discovery. Act as a user expert, deeply understanding the motivations, pain points, and goals of scientific users. Justify and prioritize improvements to existing products, focusing on delivering measurable value to scientific research and operations. Develop and maintain technical knowledge and domain expertise in drug discovery, cheminformatics, and data-driven research processes. Write clear problem statements and requirements; facilitate solution design with engineering teams. Serve as Product Owner on Agile teams or work closely with one to ensure scientific and data needs are met. Plan, design, and conduct testing activities; compile critical training and communication content for scientific end-users. Analyze data, observations, and research to generate insights that inform product strategy and decision-making. Support the Product Manager in defining and executing strategy in collaboration with engineering teams for one or more data products. Accept completed user stories, ensuring deliverables meet acceptance criteria and scientific requirements. Act as a customer champion, articulating and advocating for the needs of scientific stakeholders. Requirements Bachelor’s degree in Life Sciences, Biomedical Engineering, Chemical Engineering, Computer Science, or a related field. Two or more (2+) years building tools or data assets supporting scientific or data analytics workflows. Three or more (3+) years working with scientific users (e.g., chemists) to define requirements for data products. Experience with data analytics or data science capabilities, especially in a scientific context. Experience building ERDs, logical data models, and source-target mappings for scientific data. Hands‑on experience or working knowledge with data management services (AWS Athena, Glue, S3, Redshift, or similar). Proficiency in SQL and scientific data management. Ability to translate scientific/business problems into actionable requirements and tasks. Strong analytical problem‑solving skills. Excellent written and verbal communication skills, with the ability to engage both technical and scientific stakeholders. Ability to work independently and manage multiple complex projects simultaneously. Hard Skills data analytics data science SQL ERDs logical data models source‑target mappings data management cheminformatics product backlog management user story creation Soft Skills analytical problem‑solving communication collaboration user advocacy project management stakeholder engagement independence prioritization technical understanding facilitation #J-18808-Ljbffr Jobtailor