Lead Data Scientist – Virtual Models

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

📋 Description

• Oversee QIMA's virtual pharmacology models initiative

• Evaluate proposals and the associated datasets across QIMA’s Business Units

• Analyze data quality, structure, consistency, depth, and breadth

• Suggest one or two models with the most promising development potential

• Construct and manage data pipelines

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

• Create machine learning models and proof-of-concept prototypes

• Identify data deficiencies and propose additional experiments

• Collaborate with laboratory scientists to outline experiments, necessary data, measurements, and quality standards

• Set validation criteria and prepare models for independent scientific verification

• 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 general audiences

• Assist in preparing a model for future commercialization as a SaaS product or service that supports, replaces, or complements wet-lab assays

• Aid in the documentation and safeguarding of intellectual property

• Initially function as an individual contributor, with the potential to help develop and lead a data science team

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

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

⛳️ 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

• Demonstrated success in delivering complex machine learning projects utilizing intricate biological datasets

• Extensive experience in building data pipelines, evaluating data quality, recognizing limitations, and defining necessary additional data

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

• Exceptional communication skills and the capacity to convey complex concepts clearly to non-specialists

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

• Practical, entrepreneurial, and hands-on mindset

• Ability to work independently and take ownership of an ambiguous, new project

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

• Familiarity with cloud data platforms, such as Snowflake

• Experience with MLOps methodologies

• CV in English

🏝️ Benefits

• Opportunity to establish a new capability from scratch and influence how QIMA utilizes its biological data

• Direct access to senior leadership, laboratory specialists, and technical teams

• Independence to define the strategy and deliver measurable outcomes

• Remote work options available

• Travel opportunities to QIMA laboratories in France, Northern Ireland, and Germany, based on project requirements