Senior Data Scientist

Why Genentech

​​​​​​​We’re passionate about delivering on Our Promise to improve the lives of patients and create healthier communities for all. We foster a culture of inclusivity, integrity and creativity while boldly pursuing answers to the world’s most complex health challenges and transforming society.

Who We Are

Our Data, Analytics, and AI team is dedicated to solving complex healthcare challenges and improving patient outcomes. Data, Analytics, and AI empowers business partners across Commercial, Medical, and Government Affairs (CMG) to make impactful decisions by leveraging data, analytics, business products, and AI/ML to enable fast, targeted actions in rapidly evolving business contexts.

Data, Analytics, and AI fosters a unified understanding of customers, actions, and outcomes by integrating analytics and insights seamlessly into CMG’s evolving digital, data, and automation platforms, creating scalable solutions and eliminating silos.

In Data, Analytics, and AI, you will work as a trusted, objective advisor and expert, recommending critical decisions and actions to be taken with credibility and a focus on driving measurable impact. You will be part of a thriving culture built on collaboration and innovation.

Job Summary

The Senior Data Scientist in Data, Analytics, and AI develops, deploys, and industrializes enterprise applications leveraging Predictive Models/Large Language Models (LLMs) - Generative AI/Agentic AI to extract value from structured and unstructured data across Commercial and Medical domains. Acting as a strategic thought partner, the role involves shaping impactful business priorities, collaborating cross-functionally, and delivering actionable insights. The position requires a strong execution mindset, commitment to data quality and governance, and the ability to communicate complex findings to different audiences—all while staying at the forefront of AI innovation and aligning with Genentech’s standards and compliance. 

Key Job Responsibilities

• Drive the development, deployment and industrialization of enterprise applications using Predictive AI/Generative AI/Agentic AI to generate value from structured and unstructured data for the Commercial and Medical organizations.

• Develop a deep understanding of customers and market dynamics, and apply your technical skills to advance that knowledge and guide the organization, delivering products that help create an integrated customer experience for customers.

• Help stakeholders define clear, impactful business priorities, and where possible, use their own expertise or existing analysis/research to influence and guide.

• Act as subject matter expert for applicable Data Science and other advanced analytical methodologies, programs, and projects. Collaborate within cross‑functional teams to develop efficient Machine Learning‑based applications, gain alignment and deliver impactful business insights; engage necessary stakeholders to enable better decision‑making.

• Openly share perspectives and insights to elevate team thinking and drive a balanced, holistic point of view; effectively weigh and communicate trade‑off considerations.

• Take an enterprise mindset, linking individual responsibilities with broader organization; focus on outcomes that provide most business value.

• Demonstrate a bias for execution, self accountability, and results ownership.

• Look for opportunities for continuous improvement; engage managers and peer groups regularly for coaching, assistance, and advocacy.

• Act as a thought partner and advisor to all relevant teams and stakeholders; look for and establish opportunities for peer mentorship.

• Apply data science and other advanced analytical methodologies, using multiple data sources and tools.

• Collaborate with data science product owners/managers, data leads, ML Engineers, MLOps, and Informatics (IX) team to develop efficient machine learning-based applications, gain alignment, and deliver impactful business insights.

• Communicate findings effectively to both technical and non-technical audiences.

• Maintain high standards of data quality, security, and governance, ensuring robust documentation and adherence to best practices.

• Stay abreast of the latest advancements in data science and AI technologies, applying innovative approaches to enhance product capabilities.

• Comply with all laws, regulations, and policies that govern