Lead Data Scientist – Virtual Models

QIMA; Greater London; Híbrido; GBP 90.000 - 140.000; Jornada completa

Descripción de la vacante

QIMA is launching a new Life Sciences programme to develop virtual pharmacology models. We seek a Lead Data Scientist to own the initiative, assess datasets, build proof‑of‑concept models, and prepare solutions for internal and client use.

You will work with scientists, IT and AI experts across Europe, with potential travel to labs in France, Northern Ireland and Germany. The role is hands-on and requires a PhD, 8–10 years of data science experience, and a proven ML track record on complex

Formación

• PhD in data science, biostatistics, bioinformatics, machine learning or related field.
• 8-10 years of experience in data science, biostatistics and machine learning.
• Proven track record delivering complex ML projects using biological datasets.
• Strong experience building data pipelines, assessing data quality, and defining data needs.
• Experience working with scientists and translating scientific questions into modelling approaches.
• Excellent communication skills and ability to explain complex concepts to non-specialists.
• Ideally experience presenting work to clients, partners or external stakeholders.
• Entrepreneurial, hands-on approach and ability to work independently on new projects.

Responsabilidades

• Review and assess proposals from QIMA's Business Units.
• Examine underlying data in detail for quality, structure, depth and breadth.
• Recommend one or two models with strongest potential for development.
• Build and manage required data pipelines.
• Clean, structure, integrate and analyse complex biological datasets.
• Develop ML models and proof of concepts.
• Identify data gaps and plan additional experiments with scientists.
• Establish validation criteria and prepare models for independent validation.
• Improve models through testing and iteration.
• Ensure code, data and models are reproducible and documented.
• Present results to scientific, technical, commercial and non-specialist audiences.
• Support preparation of a model for potential commercialisation (SaaS or services).
• Contribute to IP documentation and protection.

Conocimientos

Python

R

Machine learning

Data analytics

Educación

PhD in data science / biostatistics / bioinformatics

Herramientas

Snowflake

MLOps

Descripción del empleo

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.

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;

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.

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.