Scientific Engagement Officer (UK)

Scismic is supporting a global technology company focused on transforming the research ecosystem through innovative digital solutions. The company provides a suite of tools that empower researchers and organizations to manage data, collaborate effectively, and measure impact across the research lifecycle. This is an exciting opportunity to join a mission-driven team shaping the future of scientific research.

Location: Remote

Employment Type: Full-Time

Role Overview

We are looking for a life sciences expert with extensive experience overseeing biomedical research programs in industry—skilled in crafting and executing complex experiments and resolving technical challenges—complemented by domain-focused computational and data-analysis capabilities, to join the organization in a customer-facing yet technically engaged role.

You’ll support our engagement with scientists, help define user-driven product enhancements, and serve as a translator between domain-specific research needs and AI/engineering implementations. Your input will also help define strategic areas of development for new products and capabilities.

Your ability to empathize with researchers, understand their pain points and challenges, and articulate those effectively to company technical teams will directly shape the way we support the global biomedical research community.

Key Responsibilities

• Serve as a scientific advisor and liaison between external industry researchers (specifically in the life and biomedical sciences) and internal AI/technical teams across.
• Help identify the key research pain points and challenges related to knowledge management, data processing, and literature discovery in the biomedical domain.
• Contribute in the conversation to translate user needs into clear, actionable technical requirements for AI, NLP and product development teams.
• Contribute scientific expertise to the design, testing, and evaluation of new features across platforms like Dimensions and other internal initiatives.
• Support customer engagement efforts by conducting product feedback sessions, user interviews, and workflow mapping.
• Educate internal stakeholders—including data scientists and engineers—on biomedical concepts critical to product development.
• Engage with the scientific and industry community by attending and contributing to industry conferences representing company interests, nurturing and expanding a network of collaborators and persons of interest, and staying on top of cutting-edge scientific questions.
• Collaborate closely with Product Managers, UX Researchers, and Engineering to align strategic development with authentic researcher needs.

Required Qualifications

• Advanced degree (PhD-level) in Biomedical Sciences, Biology, Bioinformatics, or a closely related field.
• Hands-on experience in biomedical research in an industry context, with a strong understanding of experimental workflows and research practices.
• Proficiency in scientific data analysis, including experience handling biological datasets or applying computational tools in a research setting.
• Excellent communication skills, with the ability to convey complex scientific concepts clearly to non-specialist audiences, including software developers and AI researchers and present in public forums, like a scientific conference.
• Demonstrated ability to work effectively across interdisciplinary teams, especially in environments where scientific insight must inform technical decisions.
• Strong organizational and time management skills, with a proactive and collaborative working style.

Desired Qualifications

• Extensive project experience in industry R&D settings, demonstrating a comprehensive understanding of complex workflows, method development, and cross-platform validation.
• Familiarity with scientific literature workflows, research communication, or knowledge discovery challenges in the biomedical domain.
• Curiosity about AI/ML applications in research (e.g., literature mining, summarization, entity recognition), and interest in collaborating with technical teams building such systems.
• Exposure to collaborative platforms or tools used across the research lifecycle (e.g., reference managers, lab notebooks, or scientific publishing platforms).
• Curiosity about product design, user experience, and shaping research tools grounded in real scientific workflows.