This is a local hire only designated position, as relocation assistance is not available for the position
Personalized Healthcare (PHC) is transforming the healthcare industry with significant emphasis on data-driven, customized healthcare for the individual patient.
This evolution has associated impacts to the way other parties in the healthcare ecosystem operate, including patients, their advocates, healthcare providers, governments, regulators, public and private payers.
PHC in both Glocal Product Strategy and Product Development are driving Roche’s PHC transformation across the enterprise to meet current and future healthcare needs in this rapidly-evolving personalized healthcare environment.
A foundational element of realizing Personalized Healthcare is the generation and analysis of high-quality real-world data (RWD).
The RWD Transformation Team within Global Product Strategy is responsible for structuring, standardizing, and ensuring semantic integration of health data acquired from disparate source systems.
As a Medical Informaticist, you will be a core member of this team, working with data from ingestion through the end-user facing visualizations to ensure accurate transmission and meaningful representation of healthcare data.
This position will partner closely across Roche experts across Pharma and Diagnostics with the Clinical, Data Science, and Engineering teams.
The collaborative work includes modeling, normalizing, organizing, and integrating structured and unstructured data from multiple sources into a standard computable repository (RWD clinico-genomic database) to drive scientific questions and clinical insights.
You will work cross-functionally and across-Group in order to ensure the highest degree of consistency possible in our RWD generation efforts.
Activities Include :
Drive the design and development of logical data models that power extraction and transformation of EHR data into RWD clinico-genomic databases.
Proactively identify and highlight opportunities for medical informatics involvement in scoping and designing precision oncology initiatives involving RWD aggregation.
Develop the processes for updating and maintaining ontologies, terminologies, and vocabularies including mapping from local to international standards when applicable.
Review & transform data from various sources, maintain quality of the data throughout the transformation process and deliver data in a standard format and structure.
Orchestrate conversations between epidemiologists, manual abstractors, and other trained clinical staff while still being able to work closely with technical engineers and data governance bodies.
Provide insight and recommendations to support novel RWD capabilities across Pharma and Dia
Comparing learnings / experiences with teams focused on other geographies to enable development of consistent, replicable approaches to developing RWD
Required Qualifications :
Masters, PhD or MD in informatics, molecular biology or a related field
Deep knowledge of standard controlled clinical vocabularies, including ICD-9 / 10, SNOMED-CT, HCPCS, NDC, RxNorm, CPT / DRG, NAACR, OncoTree, etc.
Experience working with standard -omics nomenclature like; HUGO HGNC, Gene Ontology, HGVS, dbSNP
Deep professional experience integrating data from various clinical systems such as lab information systems, EHRs, pharmacy and / or claims
2-4+ years of experience working with applied data in oncology / precision medicine
5+ years of experience with the codification of clinical data to common ontologies.
5+ years of experience with implementing, developing and expanding clinical data models (i.e. OMOP and FHIR)
5+ years of experience translating use case requirements into actionable development requirements around real world data, including data platform operational processes.
Led or co-led data modeling, terminology normalization, data curation and / or Natural Language Processing (NLP) projects
Able to solve issues arising from cross-project dependencies; creatively balance technical, resource and time constraints
Excellent verbal and written communication skills, with emphasis on relaying complex information and concepts in more relatable terms
Preferred Skills :
Knowledge representation and reasoning
Ability to write scripts (e.g. python, perl) to perform basic data manipulation
Experience with a query language such as SPARQL or SQL
Experience with a statistical package such as R