Hulu is seeking an experienced Analytics Manager to join their Subscriber Acquisition Product Marketing team in support of Non-Subscriber Product Analytics and experimentation. This role requires strong communication skills and an aptitude to work cross-functionally and partner with multiple internal teams. The Analytics Manager will be working directly with marketing, product marketing, data science, and product teams to ultimately develop, improve, test, and grow their subscription-based streaming product.
WHAT YOU'LL DO
• Own the Subscriber Acquisition Analytics & Experimentation efforts to drive strategic growth across a portfolio of products
• Implement concepts of experimental design, statistical analysis, predictive modeling/ regression analysis, propensity score analysis, and probabilistic modeling.
• Analyze experimental data to contextualize results and address business questions
• Take ownership in defining success metrics, designing, running, and analyzing experiments to make sound data-informed product recommendations and prioritization decisions that maximize business impact and enhance the user experience.
• Socialize our experimentation or measurement methodologies across multiple teams, identify new tactics or hypotheses to influence key performance metrics, unlock new opportunities for growth, and inform roadmap prioritization
• Provide thought-leadership on how to evolve current subscriber acquisition experimentation and measurement processes/tools to allow for value-adding sophisticated analyses and consistent measurement methodology
• Execute data projects from database/ETL pipeline to analysis and insights presentation
• Write efficient SQL/Python code, complex queries across extensive data sets, and build effective models to fuel analytical frameworks that drive material improvements to signup funnel KPIs and customer lifecycle metrics
• Build, analyze, and automate dashboards and reports for monitoring key subscription/engagement metrics, and summarizing pre/post experimental results
• Establish key data sets to empower operational and exploratory analysis to identify useful trends in the data and drive strategic business insights
• Discover impactful insights through funnels, cohort analyses, user segmentation, personalization, behavioral clustering, and user journey analytics
• Partner with other teams to capture, manipulate, analyze and document raw, complex data and share cohesive data stories that make sense to business and technical audiences
• Leverage organic search data to identify growth opportunities and inform product enhancements
• Validate/reconcile product data sources/quality and ensure measurement consistency across multiple data platforms
WHAT TO BRING
• 7+ years of experience within Data Analytics or Data Science with a proven track record of using large amounts of data to drive innovation in professional or educational settings
• Strong background and applied experience in experimentation, A/B testing, machine learning techniques, and meticulous statistical analyses to infer causality. Knowledge of multi-arm bandit and Bayesian approaches is a plus
• Predictive modeling experience; specifically, regression, and time-series analysis
• Strong proficiency in SQL, Python (or another data science programming language) for writing efficient queries, data manipulation, visualization, and analysis
• Strong complex excel skills and experience utilizing excel for all entailing data analyses
• Experience utilizing Google Analytics and building custom reports/dashboards
• Data visualization experience specifically utilizing Tableau
• Experience communicating the results of analyses with stakeholders/leadership teams, and working cross-functionally across different organizations
• Bachelor's degree (Masters or PhD degree in a quantitative field preferred)
• Strong and effective communication and leadership skills
• Demonstrated ability to tackle projects with a sense of ownership and an entrepreneurial spirit.
• Similar industry/domain expertise (streaming, media, entertainment, OTT)
• Search Engine Optimization experience
• BigQuery interactive analysis experience
• Experience with distributed computing (Hive/Hadoop/Spark)
• Experience creating data products and dashboards in Tableau, R Shiny, or D3
• Experience building machine learning models with demonstrated impact
• PhD or Masters degree (in quantitative or STEM field)
Jobcode: Reference SBJ-dykj3m-3-236-98-69-42 in your application.