Senior Manager – Experimentation and Digital Analytics Engineering

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed.  We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One.

Job Description

U.S. Bank is seeking an experienced Senior Manager – Experimentation and Digital Analytics Engineering to lead our experimentation and analytics engineering team.  In this role, you'll provide world-class support for A/B and multivariate testing and digital analytics implementation across our digital platforms, including web and mobile applications.

The ideal candidate will bring a combination of technical expertise, consultative ability, and relationship management skills. You should be well-versed in modern experimentation methodologies and the latest data analytics technologies.

Responsibilities:

• Lead our experimentation engineering team and collaborate across organizational boundaries to deliver randomized controlled experimentation solutions across all digital customer touchpoints—including web, iOS, and Android platforms.

• Serve as the primary point of contact and subject matter expert for all experimentation and optimization engineering efforts. Provide technical consulting and hands-on support to software developers, product managers, marketers, and other stakeholders on the design and execution of A/B/n and multivariate experiments.

• Scale experimentation engineering services to support hundreds of product and marketing teams. Develop self-service tools and define standardized processes to improve experiment velocity, trustworthiness, insight quality, and tracking.

• Define and maintain analytics data requirements. Develop implementation guidelines and ensure our websites and mobile applications are appropriately implemented, with accurate generation and reporting of key metrics.

• Integrate experimentation requirements into agile product development and CI/CD pipelines. Enable a scalable experimentation framework to test and validate new features and ideas rapidly.

• Stay current with emerging technologies and trends in experimentation and analytics. Evaluate and implement platform enhancements using a practical buy-vs-build approach.

• Explore and integrate advanced experimentation platforms beyond Adobe Target, such as Optimizely, Eppo, LaunchDarkly and other market-leading tools to enhance our experimentation capabilities.

• Drive innovation in experimentation methodologies by incorporating machine learning and AI-driven approaches to optimize and personalize user experiences.

• Collaborate with data science teams to leverage advanced analytics and predictive modeling for deeper insights and more effective experimentation strategies.

• Design and implement robust data architecture to support experimentation and analytics needs, ensuring data integrity, scalability, and accessibility.

• Develop and maintain data repositories that enable advanced analysis of experiment results, including the integration of data from multiple sources and platforms.

• Ensure data governance and compliance with industry standards

Qualifications:

• Bachelor's or advanced degree in Computer Science, Engineering, or a related field.

• 5+ years of experience in A/B testing and digital analytics experience, including platform implementation, test execution, and analysis.

Required Skills/Experience:

• Proven leadership experience in building and scaling high-performing engineering teams focused on experimentation.

• Solid understanding of the technical and statistical foundations behind randomized controlled experiments.

• Hands-on experience with leading experimentation platforms (e.g., Adobe Target, Optimizely etc.), digital analytics tools (e.g., Adobe Analytics, Google Analytics), and data visualization tools (e.g., Tableau, Looker).

• Strong SQL skills. Familiarity with web technologies (HTML, CSS) and client-side programming (JavaScript, Android, iOS) is a plus.

• Experience with data architecture, machine learning and AI technologies to enhance experimentation and analytics capabilities.

• Strong collaboration skills to work effectively with cross-functional teams, including data science, product management, and marketing.

• Expertise in d