Genentech
Biotechnology
Location: San Francisco
Please apply using this link: https://careers.gene.com/us/en/job/GENEUS202202105323EXTERNALENUS/Informatics-Analyst-Reverse-Translation-Data-Management-Lead
Job ID 202202-105323
We are seeking a talented and experienced informatics analyst to contribute to and lead data management efforts in Development Sciences Informatics (DevSci Informatics), focused on Reverse Translation efforts new and emerging data technologies like single-cell sequencing, spatial transcriptomics, digital pathology, and flow cytometry.
Who we are:
Development Sciences (DevSci) is a translational science organization that plays a critical role both in Genentech Research and Early Development (gRED) and late stage development of products at Roche. DevSci supports drug discovery and development projects across all therapeutic areas from discovery to launch (and beyond). We are poised at a unique time when large volumes of complex and varied internal and external data for DevSci areas, such as Biomarker, PK/PD, Diagnostics, Safety Assessment, and Bio-analytical, need to be readily accessible to ensure that swift analysis, interpretation, and decision making can occur. These data impact decisions in ongoing pre-clinical and clinical programs, and provide key knowledge to inform new target discovery.
The DevSci Informatics (DSI) function is accountable for leading the strategy and execution around data lifecycle management, data standards, analytics infrastructure, ongoing data operations, and informatics systems. The data management team in DSI is focused on improving data quality and ensuring data are FAIR (Findable, Accessible, Interoperable and Reusable) through the development of new processes, standards, and solutions.
Major Responsibilities and Duties:
This role will be responsible for contributing to and helping drive data lifecycle management projects that enable the storage, organization, dissemination, and analytics of data in alignment with the scientific objectives of functional groups in the DevSci organization. A primary focus of this role will be in partnering with scientific collaborators in gRED on reverse translation efforts by driving data management, processing, and preparation workflows and approaches related to new-and-emerging high-dimensional data technologies, such as single-cell sequencing, spatial transcriptomics, whole metagenomics/microbiome, digital pathology, and complex flow cytometry.
While performing this work, the candidate will collaborate extensively with senior-level scientists, directors, research associates, operations managers, clinical data managers, data scientists/analysts, data curators, and vendor representatives within a number of cross-functional gRED-wide initiatives and programs. As well, this individual will take an active role in aligning data processing and integration efforts in DevSci with global efforts at Roche. This position may or may not have direct reports.
As a member of a diverse team of informatics professionals, lead cross-data lifecycle efforts and deliver solutions that enable Reverse Translation and exploratory scientific efforts through data management processes and workflows related to new-and-emerging data technologies. Ensure DevSci data is generated, received, cataloged, structured, and analyzed in a timely and efficient manner to meet the needs of data consumers.
Partner with other data management team members who are focused on other aspects of the data lifecycle - such as data modeling, data curation, data planning, and data acquisition - to create cohesive end-to-end data flows for new-and-emerging data technologies.
Partner with leaders in software engineering, solution architecture, business analysis, and systems development - from across the department and wider gRED/Roche organization - to plan for, design, and implement technical solutions that enable reverse translation science.
Contribute to the establishment of cross-functional partnerships that ensure data accessibility, quality, integrity, and standards.
Ensure the delivery of relevant informatics solutions to meet functional and corporate goals. Communicate learnings and best practices across the organization.
Communicate strategies, ideas, goals, and progress to the data management group and the DevSci Informatics department.
Work extensively with DevSci scientists and biosample operations managers within DevSci, and collaborate frequently with clinical scientists, statisticians, data curators, terminology experts, and database specialists across the company.
Competences and Qualifications:
BA/BS/MS/PhD with 15+ years relevant experience; Preferable at least 10 years of experience in the pharmaceutical or biotech industry. Degree in a scientific discipline preferred. Advanced degree a plus.
Thorough understanding of R&D processes and the scientific data lifecycle. Evidence of business and technology acumen. Experience with scientific data management tools and techniques, informatics systems, and managing scientific stakeholder relationships.
Understanding of and experience in reverse translation science in a clinical development setting, particularly in data processing, curation, and integration of complex multi-dimensional datasets for the purpose of enabling analysis activities.
Strong background in processing, curating, and integrating complex high-dimensional biomedical/biomarker data - such as bulk RNA-Seq, Whole Exome Sequencing, Digital Pathology (e.g. IHC, H&E), Flow Cytometry, Single-cell Sequencing (e.g. TCR-Seq, CITE-Seq), Spatial Transcriptomics, Microarray, Mass Spectrometry, and Immunoassay.
Experienced working with cross-functional scientific teams, to understand their analysis requirements and to deliver data and systems solutions that enable end user analytics.
Knowledge of the UNIX operating system, and experience with a scripting language (e.g., Perl or Python) or a statistical programming environment (e.g., R or SAS) is a must. Understanding of data visualization tools, such as R Shiny, Tableau, Spotfire highly preferred.
Background in data curation, standards, ontologies, best practices for data governance, and familiarity with the FAIR (Findable, Accessible, Interoperable, and Reusable) data principles a major plus.
Experience working with CROs and managing contract services is preferred.
Excellent people and communication skills.
JOB FACTS Job Sub Category Computational Biology
Schedule Full time
Job Type Regular
