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About the Role
QIMA is launching a new program to develop virtual pharmacology models using years of laboratory data to assess molecule efficacy and support future screening activities. This hands-on role is for an experienced data scientist to own this program from inception, identify opportunities, develop proof-of-concept models, and prepare them for internal and client use.
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 experiments, including required data, measurements, and quality criteria.
- Establish clear 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 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.
- Contribute to the documentation and protection of intellectual property related to models, pipelines, and methods.
- Potentially help build and lead a team of additional data scientists as the program grows.
Requirements
- 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.
- 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 needed data.
- 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.
- Ability to work independently and take ownership of an ambiguous, new project.
- 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 (Snowflake) and MLOps practices.
Skills
- Data Science
- Biostatistics
- Machine Learning
- Data Pipelines
- Data Quality Assessment
- Biological Data Analysis
- Python
- R
- Cloud Data Platforms
- MLOps
Location
- Paris, France
Work Type
- Hybrid
Experience Level
- 8-10 years
Education Level
- PhD
About the Company
- QIMA helps clients make products consumers can trust through compliance solutions for testing, inspection, and certification (TIC).
- Our services enable supply chain agility, sustainability, and product innovation.
- We serve 30,000 businesses globally in consumer products, agri-food, and life sciences industries.
- Backed by 6,000+ dedicated Qimates worldwide, we offer local expertise and tailored support.
- QIMA is an industry leader for customer satisfaction, highlighted by an exceptional Net Promoter Score (NPS).
- Through our Life Sciences activities, we develop and deliver scientific testing and research services.