Principal Data Scientist
GenentechAbout the role
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 Principal Data Scientist develops and maintains AI-enabled data science products that leverage advanced analytics and machine learning to solve complex business challenges, uncover trends, and enable strategic decision-making. This role combines mathematical expertise, coding proficiency, and innovative problem-solving to create and deploy cutting-edge data science solutions, driving impactful outcomes across the organization.
Key Responsibilities
Apply data science and other advanced analytical methodologies, particularly in the areas of Predictive/Generative/Agentic AI using multiple data sources and tools.
Collaborate with data science product owners/managers, data leads, Machine Learning (ML) Engineers, MLOps, and Informatics (IT) 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.
Drive the next wave of development, deployment, and industrialization of Predictive AI, advanced LLM - Generative AI and Agentic AI applications
Proactively identify emerging technologies and champion their integration to address complex Commercial and Medical needs.
Translate deep market, customer, and competitive insights into forward‑looking AI strategies with senior stakeholders, ensuring solutions not only enhance the integrated customer experience but also anticipate future industry shifts.
Partner with senior leadership to refine and prioritize AI/ML initiatives, ensuring alignment with enterprise objectives. Advocate for data‑driven decision‑making and secure necessary investments in data capabilities.
Oversee complex, large‑scale ML initiatives (including multi‑source data integration and advanced model pipelines) with robust governance, scalability, and compliance frameworks.
Act as a thought leader for applicable data science to elevate the organization’s AI maturity by introducing cutting‑edge Data Science methodologies
Ensure cohesive partnerships among Data Science, ML Engineering, MLOps, Product, and Informatics (IT) teams.
Champion data‑centric culture and influence leadership to adopt forward‑thinking AI solutions enterprise‑wide.
Establish clear metrics of success for all AI/ML programs, hold teams accountable for outcomes, and proactively course‑correct when needed. Demonstrate unwavering commitment to high‑impact delivery.
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 the conduct of Genentech activities.
Who You Are
Minimum Candidate Qualifications & Experience
Bachelor's degree in Statistics, Mathematics, Computer Science, or a related quantitative field.
8 years of experience in a data science or a related
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