Lead Data Scientist – Virtual Models

This is a fully remote position, open to applicants in Spain.

📋 Description

• Evaluate and analyze proposals from QIMA’s Business Units.

• Investigate datasets for quality, organization, consistency, depth, and scope.

• Suggest one or two models with the highest potential for development.

• Construct and oversee data pipelines.

• Clean, organize, integrate, and analyze intricate biological datasets.

• Create machine learning models and proofs of concept.

• Identify data deficiencies and propose additional experiments.

• Collaborate with laboratory scientists to define experiments, data requirements, measurements, and quality standards.

• Set validation criteria and prepare models for independent scientific evaluation.

• Enhance models through iterative testing and refinement.

• Ensure that code, data, and models are reproducible, traceable, and well-documented.

• Present findings to scientific, technical, commercial, and non-specialist audiences.

• Assist in preparing models for future commercialization as SaaS products or services that support, replace, or complement wet-lab assays.

• Contribute to the documentation and safeguarding of intellectual property.

• Initially function as an individual contributor, with the possibility of aiding in the establishment and leadership of a data science team.

• Within six months, evaluate proposals and datasets, recommend the most promising projects, and establish one or two proofs of concept.

• Within 12–15 months, prepare at least one model for potential commercialization, including scientific validation, an internal interface, and comprehensive documentation or operator training.

• Work in collaboration with Managing Directors, laboratory scientists, IT and AI specialists, and independent laboratory teams.

⛳️ Requirements

• PhD in data science, biostatistics, bioinformatics, machine learning, or a related discipline.

• 8–10 years of experience in data science, biostatistics, and machine learning.

• Established history of delivering complex machine learning projects utilizing intricate biological datasets.

• Extensive experience in building data pipelines, evaluating data quality, identifying constraints, and defining further data requirements.

• Experience collaborating with scientists and translating scientific inquiries into data and modeling strategies.

• Exceptional communication skills with the ability to convey complex concepts to non-specialists clearly.

• Ideally, experience in presenting work to clients, partners, or other external stakeholders.

• A practical, entrepreneurial, and proactive mindset.

• Capability to work independently and take ownership of ambiguous and new projects.

• Proficient in Python or R, including production-quality, version-controlled coding.

• Familiarity with cloud data platforms, such as Snowflake.

• Experience with MLOps methodologies.

• CV in English.

🏝️ Benefits

• Opportunity to establish a new capability from the ground up.

• Direct access to senior leadership, laboratory experts, and technical teams.

• Independence to define the approach and achieve tangible results.

• Chance to influence how QIMA utilizes its biological data.

• Travel to QIMA laboratories in France, Northern Ireland, and Germany, depending on project requirements.