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.

• 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.

• data analytics
• data science
• SQL
• ERDs
• logical data models
• source‑target mappings
• data management
• cheminformatics
• product backlog management
• user story creation

• analytical problem‑solving
• communication
• collaboration
• user advocacy
• project management
• stakeholder engagement
• independence
• prioritization
• technical understanding
• facilitation