88-50101671 Sr. Data Scientist

Roche•South San Francisco, CA

6d•$228,000 - $329,300•Hybrid

About The Position

The Position Genentech USA, Inc. seeks a Sr. Data Scientist at its South San Francisco, CA location. Duties: Drive the development and implementation of enterprise-level applications utilizing Predictive Artificial Intelligence, Generative Artificial Intelligence, and Agentic Workflow technologies to extract business value from structured and unstructured commercial and medical data in the organization. Function as primary subject matter expert in Data Science and advanced analytics, collaborating with cross-functional teams to develop Machine Learning-based applications that deliver actionable business insights. Partner with product owners, managers, data leads, machine learning engineers, machine learning operations teams, and informatics groups to design and implement efficient artificial intelligence solutions. Develop comprehensive understanding of pharmaceutical market dynamics and customer needs to create integrated, data-driven customer experiences through technical solutions. Guide stakeholders in defining strategic business priorities through expert analysis and research, while ensuring alignment with organizational objectives. Drive innovation in artificial intelligence and data science methodologies, utilizing diverse data sources and advanced analytical tools to solve complex business challenges. Establish and maintain high standards for data quality, security, and governance, ensuring thorough documentation and adherence to industry best practices. Provide strategic guidance and mentorship to team members while fostering a culture of continuous improvement and knowledge sharing. Effectively communicate complex technical findings and recommendations to both technical and non-technical stakeholders, ensuring clear understanding of trade-offs and business impact. Maintain current knowledge of emerging artificial intelligence technologies and methodologies, implementing innovative approaches to enhance product capabilities. May telecommute up to 2 days per week. May have up to 2 subordinates.

Requirements

Master’s degree, or foreign equivalent, in Computer Science, Health Informatics, Engineering, or related field and 2 years of experience in job offered or as Data Analyst, or related position
Programming in Python or R
SQL for database management
Machine Learning & Predictive Modeling
Natural Language Processing
Healthcare Data Standardization
ETL Pipeline Development
Statistical Analysis & Research Methods
Data Quality Assessment & Validation

Responsibilities

Drive the development and implementation of enterprise-level applications utilizing Predictive Artificial Intelligence, Generative Artificial Intelligence, and Agentic Workflow technologies to extract business value from structured and unstructured commercial and medical data in the organization.
Function as primary subject matter expert in Data Science and advanced analytics, collaborating with cross-functional teams to develop Machine Learning-based applications that deliver actionable business insights.
Partner with product owners, managers, data leads, machine learning engineers, machine learning operations teams, and informatics groups to design and implement efficient artificial intelligence solutions.
Develop comprehensive understanding of pharmaceutical market dynamics and customer needs to create integrated, data-driven customer experiences through technical solutions.
Guide stakeholders in defining strategic business priorities through expert analysis and research, while ensuring alignment with organizational objectives.
Drive innovation in artificial intelligence and data science methodologies, utilizing diverse data sources and advanced analytical tools to solve complex business challenges.
Establish and maintain high standards for data quality, security, and governance, ensuring thorough documentation and adherence to industry best practices.
Provide strategic guidance and mentorship to team members while fostering a culture of continuous improvement and knowledge sharing.
Effectively communicate complex technical findings and recommendations to both technical and non-technical stakeholders, ensuring clear understanding of trade-offs and business impact.
Maintain current knowledge of emerging artificial intelligence technologies and methodologies, implementing innovative approaches to enhance product capabilities.