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Madrid, MD, Spain
Actively hiring, first seen by us 2 days agoWork setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Assess business unit proposals and examine the quality and depth of their datasets
Build and manage data pipelines and clean and analyse complex biological datasets
Develop machine learning models and proof of concepts
Define experiments with lab scientists and prepare models for independent validation
Ensure code, data and models are reproducible, traceable and documented
Examine the underlying data in detail, including its quality, structure, consistency, depth and breadth.
Build and manage the required data pipelines.
Develop machine learning models and proof of concepts.
Work with laboratory scientists to help define these experiments
Ensure that code, data and models are reproducible, traceable and properly documented.
8–10 years of experience in data science, biostatistics and machine learning;
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 the ability to explain complex concepts clearly to non-specialists;
Strong Python or R skills, including production-quality, version-controlled code. Experience with cloud data platforms (we use Snowflake) and MLOps practices.
Experience in a specific therapeutic area is not essential. The most important requirements are strong technical expertise, experience with biological data and the ability to turn complex datasets into useful, validated models.
You have: - a PhD in data science, biostatistics, bioinformatics, machine learning or a related field; - 8–10 years of experience in data science, biostatistics and machine learning;
Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
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Day 2
Early. Similar jobs usually come down between day 7 and day 55.
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Experience in a specific therapeutic area is not essential. The most important requirements are strong technical expertise, experience with biological data and the ability to turn complex datasets into useful, validated models. Strong Python or R skills, including production-quality, version-controlled code. Experience with cloud data platforms (we use Snowflake) and MLOps practices. Why join QIMA?
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Yes. We’ve followed 4 other Lead Data Scientist – Virtual Models jobs there since October 2026. 2 came down, usually after about 14 days. 2 are still up.
Large employers often post one title for several teams, so these can be separate openings.
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:
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
This role will initially be an individual contributor position. As the programme grows, you may help build and lead a team of additional data scientists.
First objectives
Within the first six months, you will be expected to:
Within 12 to 15 months, the objective will be to prepare at least one model for potential commercialisation. This should include sufficient scientific validation, an interface usable internally, and complete documentation or detailed operator training.
You have:
Experience in a specific therapeutic area is not essential. The most important requirements are strong technical expertise, experience with biological data and the ability to turn complex datasets into useful, validated models.
Strong Python or R skills, including production-quality, version-controlled code. Experience with cloud data platforms (we use Snowflake) and MLOps practices.
Why join QIMA?
This is an opportunity to build a new capability from the ground up and shape how QIMA uses its biological data. You will have direct access to senior leadership, laboratory experts and technical teams, with the autonomy to define the approach and deliver tangible results.
The role will be based in Europe and will require travel, depending on project needs, to QIMA laboratories in France, Northern Ireland and Germany.
Does this describe you? Then we want to hear from you as soon as possible! Apply now with your CV in English and we can write the next chapter of the QIMA story together!
At QIMA, we are on a mission to help our clients make products consumers can trust. We have developed compliance solutions for testing, inspection and certification (TIC) that enable supply chain agility, sustainability and product innovation. Our services are used by 30,000 businesses globally in the consumer products, agri-food and life sciences industries. Backed by 6,000+ dedicated Qimates worldwide, we bring local expertise and tailored support to every client. Our passion for service has made QIMA an industry leader for customer satisfaction, as highlighted by our exceptional Net Promoter Score (NPS).
Through our Life Sciences activities, we develop and deliver scientific testing and research services for our clients.
We are now launching a new programme to develop virtual pharmacology models. These models will use the data generated through years of laboratory work to help assess the efficacy of molecules and support future screening activities.
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Madrid, MD, Spain
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