Applied Scientist — AI Studio
Job in
Oxford, Oxfordshire, OX1, England, UK
Listed on 2026-08-18
Listing for:
John Wiley & Sons
Full Time
position Listed on 2026-08-18
Job specializations:
-
Research/Development
Data Scientist, AI Evaluation, AI Business & Operations -
IT/Tech
AI Engineer (Applied/Software), Data Scientist, AI Evaluation, AI Business & Operations
Job Description & How to Apply Below
We believe in bold ideas, diverse perspectives, and the drive to transform knowledge into impact. Here, your curiosity fuels progress, your voice shapes innovation, and your ambition helps redefine what’s possible within science and learning. We are a culture that obsesses over impact, challenges, and drives what’s next to power infinite possibilities for our customers, colleagues and society ut the Role:
The Applied Scientist serves as the scientific lead within AI Studio engagement pods, partnering with Forward Deployed Engineers to design and deliver solutions for scientific research workflows as part of Wiley’s applied AI professional services practice. This role combines deep domain expertise with applied problem-solving to translate real-world research challenges into AI-enabled solutions that are scientifically rigorous and deployable.
The position requires working directly with customers such as pharmaceutical companies, biotech firms, and materials science organizations to embed AI into evidence-intensive research processes. The Applied Scientist ensures solutions are grounded in authoritative scientific knowledge and meet rigorous standards for accuracy and reliability, while also contributing to early-stage scoping, product development, and long-term customer relationships.
Job Responsibilities:
Lead the scientific delivery of AI-driven professional services engagements, including:
Mapping customer research workflows to identify AI opportunities
Translating scientific problems into technical requirements
Evaluating AI-generated outputs for scientific accuracy and relevance
Presenting findings and solutions to senior stakeholders
Partner closely with Forward Deployed Engineers to bridge scientific and technical domains, ensuring successful solution implementation
Participate in pre-sales and early scoping discussions to validate scientific feasibility and shape customer engagements before contracts are finalized
Build and maintain trusted relationships with senior researchers and R&D leaders, identifying opportunities for repeat and expanded business
Contribute to AI Studio product development by:
Defining scientific requirements
Validating product credibility and fitness for use Providing domain expertise to support product positioning
Establish domain authority within the customer base and broader scientific community through ongoing engagement and thought leadership
Ensure all solutions leverage authoritative data sources, including peer-reviewed research, and adhere to relevant scientific and regulatory standards
Thrive in sprint-based delivery models with defined outcomes, tight timelines, and direct accountability to customers
Required Qualifications :
Advanced degree in a relevant scientific discipline (PhD preferred)
Significant post-doctoral or industry research experience (5+ years), ideally in:
Pharmaceutical or biotech organizations
Contract research organizations (CROs)
Materials science or engineering environments
Demonstrated ability to:
Evaluate AI-generated outputs for scientific accuracy, grounding, and reliability
Apply critical thinking to determine fitness of AI solutions for real-world scientific use
Experience with research workflows in evidence-intensive environments and understanding of how scientific knowledge is generated, validated, and applied
Strong communication skills, including the ability to:
Translate between scientific and technical audiences
Present complex findings to senior stakeholders
Write clearly for both expert and non-expert audiences
Experience operating outside traditional academic environments, including:
Managing ambiguous problems
Delivering against defined outcomes under time constraints
Working directly with external stakeholders
Familiarity with AI tools or applications in a research context (preferred)
Industry-specific expertise (depending on focus area), such as:
Life sciences (e.g., pharmacology, clinical research, regulatory science) and understanding of regulatory standards
Chemistry, materials science, or engineering, with experience in experimental or quantitative research
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