We like people who are different…because we’re different, too. As one of the world’s most iconic and respected nonprofits, we know what it’s like to stand out. That’s why we’re looking at you. Your background, perspective, and desire to make an impact set you apart. As we work to help St. Jude cure childhood cancer, we're calling on the game-changers, innovators and visionaries to join our family. Not just for the kids of St. Jude, but also for you. Because at ALSAC, we develop and celebrate our employees. So, bring your whole, authentic self and become part of our shared mission: Finding cures. Saving children.®

As a Sr Analyst- Digital Product Analytics, you will be responsible for:

• Designing, developing, and implementing data models with Statistical and Machine learning expertise.
• Specifying, monitoring, gathering, analyzing, and reporting all metrics related to Product initiatives including revenue, reach, and engagement metrics such as conversion rates, web behavior, etc. for the entire digital Product portfolio.
• Data Mining and Analysis from organization databases to drive optimization and improvement of product development, marketing techniques and business strategies.

To be successful in this role, you must be able to work effectively in a fluid, fast-paced environment while maintaining good communication with management and team members and be able to mentor entry level analysts. Strong communications skills, including proven writing/editing ability a must.

• Requires a Bachelor's Degree and 6+ years of experience.
• Requires experience analyzing and developing actionable insights for digital products and experiences.
• Strong communication skills to translate data and insights into a performance data story that will inform strategy and optimization.
• Self-motivated with strong intellectual curiosity; comfortable working with large data sets across multiple data sources.
• Experience in website tagging and conversion path/journey tracking, as well as, building data queries in SQL as a plus.
• Must have demonstrated experience using the tools to drive business decisions, as well as a deep understanding of the underlying technology (tagging structure, set-up, and functional capabilities).
• Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations.
• Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development, and evaluation data sets, etc.
• Track record of diving into data to discover hidden patterns and of conducting error/deviation analysis. Experience with statistical modelling / machine learning.