Data Science Lead
Location not identified
- Pay
- Pay not listed
- Work setting
RemoteLocation limits apply — work setting source
This is a remote position. We are looking for a Data Science Lead to join a high-impact AI programme operating within a strictly regulated pharmaceutical environment. The role focuses on leading the machine learning and GenAI architecture behind a production-grade compliance platform that automates regulatory validation of marketing materials. This is a strategic, enterprise-scale initiative requiring strong ownership, architectural thinking, and hands-on depth in LLM-driven systems.
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign and evolve AI and ML architecture for compliance validation workflows
Design and optimise LLM-driven retrieval and validation pipelines (RAG)
Own evaluation frameworks, benchmarking and continuous improvement loops
Implement explainability and traceability aligned with regulatory standards
Work with ML Engineers and Backend teams to productionise AI components
From the employer’s posting
Design and evolve AI and ML architecture supporting compliance validation workflows
Design and optimise LLM-driven retrieval and validation pipelines (RAG-based systems)
Own evaluation frameworks, benchmarking strategies, and continuous improvement loops
Implement explainability and traceability mechanisms aligned with regulatory standards
Collaborate closely with ML Engineers and Backend teams on productionisation of AI components
What you’ll bring
All qualificationsCore experience
- Proven experience designing and deploying LLM-based systems in production
- Practical experience with Retrieval Augmented Generation architectures
- Experience with vector databases and embedding pipelines
- Strong Python expertise and familiarity with modern AI frameworks
- Experience designing model evaluation and validation frameworks
Qualification wording
Proven experience designing and deploying LLM-based systems in production
Practical experience with Retrieval Augmented Generation architectures
Experience with vector databases and embedding pipelines
Strong Python expertise and familiarity with modern AI frameworks
Experience designing model evaluation and validation frameworks
Tools in this posting
- Python
Source — Tool mentions in context
- Experience with vector databases and embedding pipelines - Strong Python expertise and familiarity with modern AI frameworks - Experience designing model evaluation and validation frameworks
Benefits in the posting
Full benefits wording- Comprehensive healthcare
- Fully remote working model
From the employer’s posting.
Posting record
Report an errorOpen 4 monthsWe first saw this posting 149 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 3, 2026 · 149 days ago
- Recorded sightings
- 195
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
This is a remote position.
We are looking for a Data Science Lead to join a high-impact AI programme operating within a strictly regulated pharmaceutical environment. The role focuses on leading the machine learning and GenAI architecture behind a production-grade compliance platform that automates regulatory validation of marketing materials. This is a strategic, enterprise-scale initiative requiring strong ownership, architectural thinking, and hands-on depth in LLM-driven systems.
Responsibilities
- Design and evolve AI and ML architecture supporting compliance validation workflows
- Design and optimise LLM-driven retrieval and validation pipelines (RAG-based systems)
- Own evaluation frameworks, benchmarking strategies, and continuous improvement loops
- Implement explainability and traceability mechanisms aligned with regulatory standards
- Collaborate closely with ML Engineers and Backend teams on productionisation of AI components
- Drive decisions around embeddings, vector databases, and retrieval strategies
- Ensure reproducible, testable, and high-quality AI workflows
- Support scaling the platform into an enterprise-grade AI solution
- Lead technical discussions across product, engineering, and compliance stakeholders
Requirements
- Strong hands-on background in Data Science and applied Machine Learning
- Proven experience designing and deploying LLM-based systems in production
- Practical experience with Retrieval Augmented Generation architectures
- Experience with vector databases and embedding pipelines
- Strong Python expertise and familiarity with modern AI frameworks
- Experience designing model evaluation and validation frameworks
- Ability to operate in regulated or compliance-heavy environments
- Strong ownership mindset and ability to influence architectural decisions
- Confident communication skills in cross-functional environments
Nice to have
- Experience in pharmaceutical, healthcare, or other regulated industries
- Exposure to explainable AI methodologies or frameworks
- Experience with document intelligence and NLP-heavy pipelines
- Background in enterprise-scale AI platforms rather than proof-of-concept environments
Benefits
- Solid, competitive salary
- Work in a multinational environment on international projects
- Comprehensive healthcare
- Long-term B2B contract with a stable project pipeline
- Fully remote working model
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Location not supplied.
This is a remote position. We are looking for a Data Science Lead to join a high-impact AI programme operating within a strictly regulated pharmaceutical environment. The role focuses on leading the machine learning and GenAI architecture behind a production-grade compliance platform that automates regulatory validation of marketing materials. This is a strategic, enterprise-scale initiative requiring strong ownership, architectural thinking, and hands-on depth in LLM-driven systems.
More source context
- Long-term B2B contract with a stable project pipeline - Fully remote working model
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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