Lead Data Scientist – Virtual Models

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h3Company Description /h3 pAt 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). /p pThrough our Life Sciences activities, we develop and deliver scientific testing and research services for our clients. /p pWe are now launching a new programme to develop bvirtual pharmacology models /b. These models will use the data generated through years of laboratory work to help assess the efficacy of molecules and support future screening activities. /p h3Job Description /h3 pWe are looking for a bLead Data Scientist - Virtual Models /b to take ownership of this programme from the start. /p pThis 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. /p h3Initial Applications May Include Models Related To /h3 ul liskin /li lihair follicles /li lilongevity /li liprostate cancer /li liimmunology /li /ul pYou 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. /p h3Key Responsibilities /h3 ul liReview and assess proposals from QIMA’s Business Units. /li liExamine the underlying data in detail, including its quality, structure, consistency, depth and breadth.



/li liRecommend one or two models with the strongest potential for development, subject to approval by the CEO of QIMA Life Sciences. /li liBuild and manage the required data pipelines. /li liClean, structure, integrate and analyse complex biological datasets. /li liDevelop machine learning models and proof of concepts. /li liIdentify 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. /li liEstablish clear validation criteria and prepare models for independent scientific validation. /li liImprove the models through repeated testing and iteration. /li liEnsure that code, data and models are reproducible, traceable and properly documented. /li liPresent results clearly to scientific, technical, commercial and non-specialist audiences. /li liSupport the preparation of a model for future commercialisation, either as a SaaS product or as a service supporting, replacing or complementing wet-lab assays. /li liContribute to the documentation and protection of intellectual property related to the models, pipelines and methods. /li /ul pThis role will initially be an individual contributor position. As the programme grows, you may help build and lead a team of additional data scientists. /p h3First objectives /h3 pWithin the first six months, you will be expected to: /p ul liassess the main model proposals and their underlying datasets; /li lirecommend the one or two strongest projects; /li liestablish a proof of concept for one or two models. /li /ul pWithin 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. /p h3Qualifications /h3 ul lia PhD in data science, biostatistics, bioinformatics, machine learning or a related field; /li li8-10 years of experience in data science, biostatistics and machine learning; /li lia proven track record of delivering complex machine learning projects using complex biological datasets; /li listrong experience building data pipelines, assessing data quality, identifying limitations and defining what additional data is needed; /li liexperience working with scientists and translating scientific questions into data and modelling approaches; /li liexcellent communication skills and the ability to explain complex concepts clearly to non-specialists; /li liideally, experience presenting work to clients, partners or other external stakeholders; /li lia practical, entrepreneurial and hands-on approach; /li lithe ability to work independently and take ownership of an ambiguous, new project. /li /ul pExperience 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. /p pStrong Python or R skills, including production-quality, version-controlled code. Experience with cloud data platforms (we use Snowflake) and MLOps practices. /p h3Why join QIMA? /h3 pThis 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. /p pThe role will be based in Europe and will require travel, depending on project needs, to QIMA laboratories in France, Northern Ireland and Germany. /p #J-18808-Ljbffr

Vedi l’offerta su Go Lavoro: golavoro.it/annuncio-lavoro/8lm1jl