Data Analytics Senior Manager

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 Data Analyst Senior Manager plays a key role in supporting the development and optimization of analytical products by delivering data-driven insights and actionable recommendations. This role involves analyzing complex datasets, designing scalable solutions for data integration and visualization, and collaborating closely with modular analytical product teams to address specific business and product needs. By ensuring data quality, creating intuitive dashboards, and supporting advanced analytics initiatives, the Data Analyst enables stakeholders to make informed decisions. Working flexibly within an agile, product-focused framework, this position fosters a culture of continuous improvement and innovation while contributing to the measurable impact and success of analytic products.

Key Responsibilities

• Drive analysis of large and complex datasets to generate actionable insights that enhance analytic product performance and contribute to measurable business impact.

• Demonstrate proficiency in translating business questions into analytical frameworks and providing recommendations.

• Leverage deep expertise in tools like Adobe Analytics and Google Analytics to enhance data analysis and reporting capabilities.

• Autonomously operate and manage all stakeholders (with limited manager guidance received through pro-active upward management).

• Create and deliver intuitive dashboards, visualizations, and reports to support decision-making and track product outcomes effectively.

• Collaborate with a cross-functional product team, including business product owner, product managers, program managers, project managers, data engineers, and technology roles to understand business needs and design analytics solutions.

• Aggregate and synthesize data from multiple internal and external sources, such as sales data, CRM platforms, market research, and competitive intelligence, ensuring alignment with product goals.

• Ensure data quality, integrity, and compliance with industry regulations and internal standards.

• 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.

• 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.

Who You Are

Minimum Candidate Qualifications & Experience

• Bachelor's or Master’s degree in Computer Science, Information Systems, Data Science, or related field.

• 5 years of experience in data analysis, business intelligence, or related roles.

• Experience with BI and web & mobile analytics tools (e.g. Adobe Analytics, Google Analytics).

• Proficiency in data analysis tools such as SQL, R, Excel, or similar.

• Experience with data visualization tools like Tableau, Power BI, or Qlik.