88-50100101 Senior Data Sciences Product Leader

Roche • South San Francisco, CA

8d • $177,360 - $218,400 • Hybrid

About The Position

Genentech, Inc. seeks a Senior Data Sciences Product Leader at its South San Francisco, CA location. Duties include identifying, designing, and executing fit-for-purpose data management solutions adhering to F.A.I.R. principles for medical science uses. This role involves developing systems for organizing data to analyze, identify, and report trends, and working in data life-cycle management from acquisition through curation of clinical data for research, development, and evidence generation. The position requires designing, documenting, testing, and implementing clinical data studies for novel drug therapies, as well as working on non-study/molecule-enabling projects to improve data acquisition, processing, and analysis efficiency during the clinical trial lifecycle. Responsibilities also include developing risk management strategies, managing timelines for study and project delivery, implementing new technologies, and ensuring data quality and compliance with pharma industry regulations. The role involves organizing and integrating data from various sources, analyzing interrelationships between clinical and non-clinical data, and defining logical aspects of datasets. Collaboration with stakeholders to understand data insight needs and offer Data Management solutions is key. The position utilizes data surveillance tools and strategies for aggregate level reviews to identify patterns and anomalies, ensuring high-quality results. A strong understanding of the data flow from collection to analysis is required, along with preparing reports for regulatory authorities. Developing data transfer agreements with vendors, ensuring the use of standards, fit-for-purpose data models, and transfer intervals is also part of the role. The position may telecommute 1 day per week.

Requirements

• Master’s degree in Bioengineering, Biomedical Engineering, Electrical and Computer Engineering or closely related field.
• Programming in Python and R in order to process clinical, real-world data and operational data
• Using R, Python and Statistical Machine Learning to create insights through advanced data analytics
• Data Modeling to create visualizations to aid in the processing of multiple data types from multiple sources
• Performing computational science using mathematical models, computer simulations, information and signal processing, and statistical analyses.

Responsibilities

• Identify, design and execute fit for purpose data management solutions, adhering to F.A.I.R. (Findable, Accessible, Interoperable, Reusable) principles for medical science uses.
• Develop systems for organizing data to analyze, identify, and report trends.
• Work in data life-cycle management right from acquisition through curation of clinical data for use in exploratory research, clinical development and evidence generation.
• Design, document, test and implement clinical data studies for novel drug therapies.
• Work on non-study/molecule-enabling projects that aid in improving the quality and efficiency of data acquisition, processing and analysis processes during clinical trial lifecycle.
• Develop risk management strategies and proactively manage timelines to ensure successful oversight and delivery of studies, projects and coding responsibilities, including the implementation and adoption of new technologies.
• Ensure a high quality of data and compliance with applicable pharma industry regulations and standards.
• Organization and integration of data collected from various sources.
• Analyze the interrelationships of clinical and non-clinical data and define logical aspects of datasets.
• Collaborate with stakeholders to understand their data insight needs and offer Data Management solutions.
• Use data surveillance tools and strategies to provide aggregate level reviews designed to identify patterns and anomalies in the data to ensure high quality results.
• Demonstrate a strong understanding of the data flow from collection through to analysis prepare reports of clinical trial studies for internal validation and cross validation studies for filing to health regulatory authorities like U.S Food and Drug Administration and European Medicine Agencies.
• Develop data transfer agreements with vendors ensuring use of standards, fit-for-purpose data models and transfer intervals.

Benefits

• A discretionary annual bonus may be available based on individual and Company performance.
• Benefits detailed at the link provided below. Benefits (https://roche.ehr.com/default.ashx?CLASSNAME=splash )

What This Job Offers

• Job Type: Full-time
• Career Level: Senior