Senior Informatics Analyst, Development Sciences Informatics


  • San Francisco, CA
  • Permanent
  • Full-time
  • 3 months ago
We are seeking a talented and experienced Senior Informatics Analyst to lead data management and curation efforts in Development Sciences Informatics (DevSci Informatics) through the development of new and/or improved data lifecycle processes, standards, models, terminologies, and ontologies for existing and emerging data types.

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 preclinical and clinical programs, and provide key knowledge to inform new target discovery.

DevSci Informatics is accountable for leading the strategy and execution around data lifecycle management, data standards, analytics infrastructure, ongoing data operations and informatics systems.

Major Responsibilities and Duties:

This role is responsible for contributing to and helping drive data life cycle management projects that enable the storage, organization, dissemination, and analytics of data in alignment with the scientific objectives of the Biomarker Development functional groups in the Development Sciences (DevSci) organization. In the process of performing this work, the candidate will collaborate extensively with scientists, research associates, operations managers, clinical data managers, data scientists/analysts, and vendor representatives. As well, this individual will take an active role in aligning data standards across 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 global and cross-functional efforts to provide informatics solutions and services around data management and data curation. Ensure delivery of relevant informatics solutions to meet functional and corporate goals.

Define and implement data management strategies to manage new and emerging data types.

Lead data governance, standardization, and curation initiatives across gRED.

Contribute to the establishment of cross-functional partnerships that ensure data accessibility, quality, integrity, and standards.

Communicate learnings and best practices across the organization and informatics collaborative partners.

Communicate strategies, ideas, goals and progress to the data management group, the DevSci Informatics department, senior executives, and collaborative internal and external partners. Work extensively with biomarker scientists and biosample operations managers within DevSci, and collaborate frequently with clinical scientists, statisticians, and database specialists across the company.

May supervise, mentor, and provide career development for staff members in the data management team.

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.

Deep and in-depth understanding of R&D processes and scientific data life cycle. Evidence of business and technology acumen. Experience with the scientific data management strategy development and execution, and managing cross-functional scientific stakeholder relationships.

Knowledge of the UNIX operating system, a scripting language (e.g., Perl or Python), and a statistical programming environment (e.g., R or SAS) is a must.

Excellent knowledge of informatics and data management tools and techniques. Strong knowledge of genomic data and biosample management a plus.

Strong background in data standards, ontologies, and best practices for data governance. Familiarity with the FAIR (Findable, Accessible, Interoperable, and Reusable) data guiding principles a major plus.

Up-to-date knowledge of data technology trends and utilities in general, in particular for pharmaceutical research and development. Experienced with informatics systems, relational and non-relational databases, scripting languages, and data visualization tools. Working knowledge of scientific research applications development cycles, data management techniques and infrastructure requirements.

Experience working with CROs and managing contract services.

Excellent people and communication skills.