Job Description – Senior Lead Revenue Operations Analyst,  San Francisco


Do you geek out at the intersection of statistics and storytelling? Are you passionate about finding the story the data is telling, and using it to help drive key decisions? Are you interested in helping shape the direction of the world’s largest health and fitness community?


Let’s talk.


The Under Armour Connected Fitness team, the world’s most integrated digital health suite of apps, devices, and apparel, needs an experienced analyst/data scientist to join our Revenue Operations team in our downtown SF office.  As part of the Revenue Operations team that optimizes revenue opportunities across the Connected Fitness eco-system, the Senior Lead Product Analystwill help guide development and innovation of new features and products through deep data analytics and consumer insights. They will coordinate with the media and marketing functions to maximize the value of the digital consumer by ensuring that Under Armour provides the highest possible value to that consumer. They will perform: 


  • In depth analysis of revenue products, including
    • User behavior analysis
    • Overseeing proper design and implementation of A/B tests
    • Segmentation/funnel studies
    • Churn and conversion modeling
    • Clustering/User Profiles
  • Success metrics development
    • Revenue KPIs and other key metric definitions
    • Data source analysis and requirements definition
    • Data flow algorithm optimization and automation
    • Reporting and visualization
  • Integration with Engineering teams
    • Requirements building for data infrastructure
    • Instrumentation definition with development engineers
    • ETL prototype development
  • Complex data analysis tasks
    • Machine learning models (classification, regression, clustering)
    • LTV (lifetime value) calculation
    • Data transformation scripting
    • Conversion of data into stories for broad audience consumption


The most successful applicants will have experience with the following:


  • 10 years+ in data analytics/data science
  • Advanced degree in an analytical field (predictive analytics, data science, business, statistics, hard or social sciences)
  • Advanced SQL skills
  • Dexterity with an advanced statistical package (e.g. Pandas, SciPy, SciKitLearn)
  • Programming in a scripting environment (e.g. Jupyter notebooks)
  • Tableau/Looker visualization
  • A/B testing including optimal sample size and experiment duration determination, significance of results calculation
  • Communicating data stories in written and verbal form to wide audiences of varying levels of sophistication

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