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Data Science Lead

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Work setup
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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.
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Employment
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What you’ll work on

Full 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

From the employer’s posting
Responsibilities Design and evolve AI and ML architecture supporting compliance validation workflows Design and optimise LLM-driven retrieval and validation pipelines (RAG-based systems)
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
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

What you’ll bring

All qualifications

Core experience

  • Proven experience designing and deploying LLM-based systems in production
  • Experience in pharmaceutical, healthcare, or other regulated industries
  • Experience with document intelligence and NLP-heavy pipelines
  • Practical experience with Retrieval Augmented Generation architectures
  • Experience with vector databases and embedding pipelines
  • Strong Python expertise and familiarity with modern AI frameworks
Qualification wording
Proven experience designing and deploying LLM-based systems in production
Experience in pharmaceutical, healthcare, or other regulated industries
Experience with document intelligence and NLP-heavy pipelines
Practical experience with Retrieval Augmented Generation architectures
Experience with vector databases and embedding pipelines
Strong Python expertise and familiarity with modern AI 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.

Job description

View original posting ↗

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


Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on madiffpl.zohorecruit.com. The employer’s form will show what is required.

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Source & posting history

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Pay

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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

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Status in our records
Active
First seen by us
Jun 3, 2026
Recorded sightings
125
Last seen by us
Sep 30, 2026

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