Data Analytics Senior Manager - Forecasting Suite

The Position

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, Digital and Analytics team is dedicated to solving complex healthcare challenges and improving patient outcomes. Data, Digital and Analytics 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, Digital and Analytics 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, Digital and Analytics, 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 Data Analytics Senior Manager (Forecasting) plays a key role in supporting the development and optimisation of forecasting tools, products, and processes. This is an individual contributor role.

You will be responsible for designing, coding, and prototyping the analytical logic that powers our forecasting tools. Working alongside product managers and therapy area forecasters, you will dig deep into complex pharmaceutical datasets to build scalable solutions, ensuring our forecasting products rely on robust, high‑quality logic. You will also play a critical role in visualising model outputs to ensure they are interpretable and actionable for business stakeholders.

• Drive analysis of large and complex datasets to generate actionable insights that enable forecasting product development, enhance product performance and contribute to measurable business impact.
• Lead and drive the building and scaling of new forecasting models and tools to support driverless and driver based forecasting and trending models and tools.
• Demonstrate proficiency in translating business questions into analytical frameworks and providing recommendations.
• Aggregate and synthesize data from multiple internal and external sources, such as claims data, EMR data, sales data, CRM platforms, market research, and competitive intelligence to reconcile and refine existing epidemiology models.
• Ensure data quality, integrity, and compliance with industry regulations and internal standards.
• Autonomously operate and manage all stakeholders (with limited manager guidance received through pro‑active upward management).
• Collaborate with a cross‑functional product team, including business product owner, product managers, programme managers, project managers, data engineers, and technology roles to understand business needs and design analytics solutions.
• Guide and collaborate with remote teams to ensure alignment and quality in analytics deliverables.
• Partner with data science teams to implement machine learning algorithms and statistical analyses when needed.
• Present insights and recommendations to senior leaders and stakeholders in a clear and impactful manner.
• Influence decision‑making by connecting analytical findings to business goals and strategies.
• Comply with all laws, regulations and policies that govern the conduct of Genentech activities.

• Bachelor's or Master’s degree in Business Analytics, Statistics, Maths, Data Science, or related field.
• 5+ years of experience in data analysis, business intelligence, or related roles.
• Proficiency in data analysis tools such as Python, SQL, R, Excel, or similar.
• Experience with building forecast models and machine learning including model drift modelling, predictive algorithm deployment, MLOps and statistical trending.
• Familiarity with cloud‑based analytics platforms (e.g. AWS, Snowflake,…