Lead Data Scientist – Virtual Models

• Take ownership of QIMA’s virtual pharmacology models programme
• Assess proposals and underlying datasets across QIMA’s Business Units
• Examine data quality, structure, consistency, depth and breadth
• Recommend one or two models with the strongest development potential
• Build and manage data pipelines
• Clean, structure, integrate and analyse complex biological datasets
• Develop machine learning models and proof-of-concept models
• Identify data gaps and recommend additional experiments
• Work with laboratory scientists to define experiments, required data, measurements and quality criteria
• Establish validation criteria and prepare models for independent scientific validation
• Improve models through repeated testing and iteration
• Ensure code, data and models are reproducible, traceable and properly documented
• Present results to scientific, technical, commercial and non-specialist audiences
• Support preparation of a model for future commercialisation as a SaaS product or service supporting, replacing or complementing wet-lab assays
• Contribute to documentation and protection of intellectual property
• Initially work as an individual contributor, with potential to help build and lead a data science team
• Within six months, assess proposals, recommend the strongest projects and establish one or two proofs of concept
• Within 12–15 months, prepare at least one model for potential commercialisation, including scientific validation, an internal interface and complete documentation or detailed operator training

• PhD in data science, biostatistics, bioinformatics, machine learning or a related field
• 8–10 years of experience in data science, biostatistics and machine learning
• Proven track record of delivering complex machine learning projects using complex biological datasets
• Strong experience building data pipelines, assessing data quality, identifying limitations and defining what additional data is needed
• Experience working with scientists and translating scientific questions into data and modelling approaches
• Excellent communication skills and ability to explain complex concepts clearly to non-specialists
• Ideally, experience presenting work to clients, partners or other external stakeholders
• Practical, entrepreneurial and hands-on approach
• Ability to work independently and take ownership of an ambiguous, new project
• Strong Python or R skills, including production-quality, version-controlled code
• Experience with cloud data platforms, including Snowflake
• Experience with MLOps practices
• CV in English

• Opportunity to build a new capability from the ground up and shape how QIMA uses its biological data
• Direct access to senior leadership, laboratory experts and technical teams
• Autonomy to define the approach and deliver tangible results
• Remote work available
• Travel opportunities to QIMA laboratories in France, Northern Ireland and Germany, depending on project needs