Clinical Data Manager
pHospitals hold huge amounts of clinical data that could answer real research questions, yet most of it sits unused. It is scattered across incompatible systems, and sharing it raises serious privacy issues: the classic way, copying patient data into a central database, no longer holds up. /p pAt Agora Labs we're building a new way to do Real-World Evidence: /p pbData stays where it is. /b It never leaves the hospital. What reaches researchers is privacy-preserving. /p pbPrivacy guaranteed by math, not just procedures. /b We use differential privacy, synthetic data and mathematical anonymization, so researchers get high clinical and statistical value without exposing a single patient. /p pbInternational standards from day one. /b Hospital data are restructured into bOMOP /b and bHL7 FHIR /b, so they are comparable across centers and countries. /p pbBuilt for what comes next. /b Federated learning and AI applied to clinical research, with data made truly usable, the way the bEuropean Health Data Space (EHDS) /b envisions. /p pYour role is to make all of this work in the real world, inside real hospitals. /p pbLevel /b /p pHands-on work with clinical or hospital data. We care about what you can do, not the years on your CV. /p p€29,000–38,000 gross per year, depending on experience /p pbWhere /b /p pRemote, with some in-person days and travel to hospitals across Italy (~25%) /p pbContract /b /p pPermanent, with a probation period to get to know each other Start: ASAP /p h3What you'll actually do /h3 pbProtocol to data: /b read a study protocol and work out which variables it needs,
ranked by priority and with the clinical reasoning behind each one. /p pbData hunting: /b find where those data live in the hospital (clinical records, labs, pharmacy, pathology, registries) and who owns them. /p pbFeasibility: /b check with clinicians and data managers what exists, over which period, for how many patients and how complete it is. /p pbStandards: /b help map hospital data to OMOP and FHIR, and document every mapping decision. /p pbData quality: /b profile first data extracts and spot what doesn't add up. /p pbData Catalogue: /b keep our map of hospital data up to date, so every new project starts from what we already know. /p pbIndustry to hospital: /b turn a pharma or medtech request into a project a hospital can actually deliver. /p h3A week in the role /h3 pbMonday /b /p pA new protocol arrives. You turn it into a list of variables, ranked by priority. /p pbTuesday /b /p pA call with a hospital data manager: do those variables exist, and for how many patients? /p pOn site at a hospital, with clinicians and IT. /p pbThursday /b /p pYou profile a first extract, check how it maps to OMOP and flag the gaps.
/p pbFriday /b /p pYou update the Data Catalogue and share what you learned with the product and tech teams. /p h3What you’ll learn /h3 pHow hospital data really work, from the clinical record to the database. How a real-world evidence study is designed. OMOP and FHIR in practice. How privacy technologies (differential privacy, synthetic data, federated approaches) are applied to real clinical data. You'll work day to day with the Head of Clinical Data Valorization, with real responsibility from the start, and with a clear path toward Data Strategy, Data Stewardship or RWE Project Management. /p pare at ease talking to a doctor, an IT engineer and a business person, sometimes all in the same day; /p plearn fast and don't need perfect instructions; /p pare precise about definitions and data, and pragmatic about everything else; /p psee a problem, say so, and propose a fix. /p h3It's probably not for you if… /h3 pyou want a fixed routine: we're a startup, and many things we're building together; /p pyou'd rather not travel: hospitals are where the real work happens; /p pyou want to train AI models all day: you'll work alongside our data science team, but your job is to understand the data, not to model it. /p h3What you need /h3 pbMust-haves: /b a Master's degree in a life-sciences, health or data field; fluent Italian and professional English; experience with clinical or hospital data. /p pbNice to have: /b SQL, Python or R; familiarity with OMOP, FHIR and clinical coding systems such as ICD, SNOMED CT or LOINC; ethics committee submissions or GCP training; a third language. /p #J-18808-Ljbffr
ranked by priority and with the clinical reasoning behind each one. /p pbData hunting: /b find where those data live in the hospital (clinical records, labs, pharmacy, pathology, registries) and who owns them. /p pbFeasibility: /b check with clinicians and data managers what exists, over which period, for how many patients and how complete it is. /p pbStandards: /b help map hospital data to OMOP and FHIR, and document every mapping decision. /p pbData quality: /b profile first data extracts and spot what doesn't add up. /p pbData Catalogue: /b keep our map of hospital data up to date, so every new project starts from what we already know. /p pbIndustry to hospital: /b turn a pharma or medtech request into a project a hospital can actually deliver. /p h3A week in the role /h3 pbMonday /b /p pA new protocol arrives. You turn it into a list of variables, ranked by priority. /p pbTuesday /b /p pA call with a hospital data manager: do those variables exist, and for how many patients? /p pOn site at a hospital, with clinicians and IT. /p pbThursday /b /p pYou profile a first extract, check how it maps to OMOP and flag the gaps.
/p pbFriday /b /p pYou update the Data Catalogue and share what you learned with the product and tech teams. /p h3What you’ll learn /h3 pHow hospital data really work, from the clinical record to the database. How a real-world evidence study is designed. OMOP and FHIR in practice. How privacy technologies (differential privacy, synthetic data, federated approaches) are applied to real clinical data. You'll work day to day with the Head of Clinical Data Valorization, with real responsibility from the start, and with a clear path toward Data Strategy, Data Stewardship or RWE Project Management. /p pare at ease talking to a doctor, an IT engineer and a business person, sometimes all in the same day; /p plearn fast and don't need perfect instructions; /p pare precise about definitions and data, and pragmatic about everything else; /p psee a problem, say so, and propose a fix. /p h3It's probably not for you if… /h3 pyou want a fixed routine: we're a startup, and many things we're building together; /p pyou'd rather not travel: hospitals are where the real work happens; /p pyou want to train AI models all day: you'll work alongside our data science team, but your job is to understand the data, not to model it. /p h3What you need /h3 pbMust-haves: /b a Master's degree in a life-sciences, health or data field; fluent Italian and professional English; experience with clinical or hospital data. /p pbNice to have: /b SQL, Python or R; familiarity with OMOP, FHIR and clinical coding systems such as ICD, SNOMED CT or LOINC; ethics committee submissions or GCP training; a third language. /p #J-18808-Ljbffr