Senior Data Scientist

Roche • South San Francisco, CA

1d • Onsite

About The Position

The Opportunity The Data, Analytics, and AI team is dedicated to solving complex healthcare challenges and improving patient outcomes by empowering business partners across Commercial, Medical, and Government Affairs (CMG) to make impactful decisions. This is achieved by leveraging data, analytics, business products, and AI/ML for fast, targeted actions, fostering a unified understanding of customers, actions, and outcomes through the seamless integration of insights into digital, data, and automation platforms, and eliminating silos. In this team, members work as trusted, objective advisors and experts, recommending critical decisions and actions with credibility and a focus on driving measurable impact, all within 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.

Requirements

• Bachelor's degree in Statistics, Mathematics, Computer Science, or a related quantitative field.
• 5 years of experience in data science or related roles.
• Proficiency in programming languages such as Python, R.
• Knowledge of SQL for database management.
• Understanding of statistical methods and machine learning algorithms.
• Excellent verbal and written communication skills, with the ability to present complex data analyses to non-technical stakeholders.
• Strong critical thinking and problem-solving abilities, with a detail-oriented approach to data analysis.

Nice To Haves

• Experience working with large and complex data sets in collaboration with business and analytics teams.
• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Contributions to open source projects or publications in data science.
• Experience in healthcare, pharmaceutical, or highly regulated industries.
• Relevant certifications in data science, machine learning, or AI technologies (e.g., Certified Analytics Professional, AWS or similar certifications).
• LLM & Gen AI Expertise: At least 2 years of experience implementing LLMs (e.g., GPT, BERT, Claude, etc.) and Generative AI solutions in production environments, specifically for enterprise-level data processing, information extraction, automation, and decision-making, with measurable business outcomes.
• Machine Learning & Deep Learning: Strong expertise in Machine Learning and Deep Learning techniques, with a specific focus on NLP-related architectures such as Transformers for text classification, sequence-to-sequence tasks, summarization, and question answering.
• Demonstrated working knowledge of recent advancements in LLMs, Agentic Workflow Design Patterns, and open-source frameworks like LangChain, LlamaIndex, LangGraph etc.
• In-depth knowledge of Prompt Engineering and Chain-of-Thought Prompting strategies for optimizing LLM-based solutions in production.
• Experience working with large, complex data using Hadoop or Spark or any other big data platforms.
• Proficiency with industry-standard programming languages such as R or Python.
• Experience with other Data Science and cloud-computing tools and platforms (AWS, GCP, etc.).
• Experience with deploying LLMs via third-party API service providers like Open AI, Anthropic, AWS Bedrock etc.
• Proficiency using ML in a variety of contexts such as insight generation, ROI calculation, text classification, clustering etc.
• Experience with data visualization tools such as tableau, and/or Qlik, and/or data studio etc.
• Experience translating research or analysis to communicate (in presentations and in writing) concise and compelling business stories that influence decisions and strategy.

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees