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Lead Data Scientist – Virtual Models
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Job Description
We are looking for a Lead Data Scientist – Virtual Models to take ownership of this programme from the start. This is a hands-on role for an experienced data scientist who wants to build something new.
You will assess existing datasets across QIMA ’s Business Units, identify the most promising opportunities, develop proof-of-concept models and prepare them for use by internal teams and, ultimately, by clients.
Initial applications may include models related to: skin; hair follicles; longevity; prostate cancer; immunology. You will work closely with Managing Directors, laboratory scientists and QIMA ’s IT and AI experts. Scientific validation will be carried out in collaboration with independent laboratory teams.
Key responsibilities Review and assess proposals from QIMA ’s Business Units. Examine the underlying data in detail, including its quality, structure, consistency, depth and breadth. Recommend one or two models with the strongest potential for development, subject to approval by the CEO of QIMA Life Sciences.
Build and manage the required data pipelines. Clean, structure, integrate and analyse complex biological datasets. Develop machine learning models and proof of concepts. Identify data gaps and recommend additional experiments where needed.
Work with laboratory scientists to help define these experiments, including the required data, measurements and quality criteria. Establish clear validation criteria and prepare models for independent scientific validation. Improve the models through repeated testing and iteration.
Ensure that code, data and models are reproducible, traceable and properly documented. Present results clearly to scientific, technical, commercial and non-specialist audiences.
Support the preparation of a model for future commercialisation, either as a SaaS product or as a service supporting, replacing or complementing wet-lab assays. Contribute to the documentation and protection of intellectual property related to the models, pipelines
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