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Lead Data Scientist – Virtual Models

Pay
Pay not listed
Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
From the employer’s 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 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

From the employer’s posting
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.

What you’ll bring

All qualifications

Core experience

  • 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.

Preferred experience

  • Experience in a specific therapeutic area is not essential.
Qualification wording
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.
Education & alternatives
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;
Apply at QIMA

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20262 days ago
Recorded sightings
3
Last seen by us
Nov 4, 2026

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How this job compares

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Day 2

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QIMA is hiring

3 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Scientist hiring is picking up
  • Takes jobs down quickly
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  • Python
  • R
  • Snowflake
Where the posting names them
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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Has QIMA posted this job before?

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.

  1. LondonStill up after 16 days, first seen Oct 19
  2. ParisCame down after 14 days, first seen Oct 19
  3. RomeCame down after 14 days, first seen Oct 19
  4. ColeraineStill up after 2 days, first seen Nov 2
  5. This jobUp 2 days so far, first seen Nov 2

Large employers often post one title for several teams, so these can be separate openings.

Job description

View original posting ↗

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 and methods.

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:

  • assess the main model proposals and their underlying datasets;
  • recommend the one or two strongest projects;
  • establish a proof of concept for one or two models.

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.

Qualifications

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;
  • a 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 the ability to explain complex concepts clearly to non-specialists;
  • ideally, experience presenting work to clients, partners or other external stakeholders;
  • a practical, entrepreneurial and hands-on approach;
  • the ability to work independently and take ownership of an ambiguous, new project.

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.

 

Additional Information

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!

Company Description

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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