Senior Data Analyst, Platform Analytics
New York, NY US
Comprised of Disney's international media businesses and the Company's various streaming services, the Direct-to-Consumer and International (DTCI) segment aligns technology, content and distribution platforms to expand the Company's global footprint and deliver world-class, personalized entertainment experiences to consumers around the world.
The Walt Disney Company's Direct-to-Consumer and International segment (DTCI) is a global, multiplatform media, technology and distribution organization for high-quality content created by Disney's Studio Entertainment and Media Networks groups.
DTCI includes Disney's international media operations and the Company's direct-to-consumer businesses globally, including the upcoming Disney-branded direct-to-consumer streaming service, the Company's ownership stake in Hulu, and the ESPN+ sports streaming service, programmed in partnership with ESPN. BAMTECH Media, developer of the ESPN+ and Disney-branded streaming platforms, oversees all consumer-facing digital technology and products across the Company as part of the Direct-to-Consumer and International segment.
Disney Streaming Services (DSS) is seeking a Data Scientist to focus on informing business decisions through data modeling, analysis and insights generation. You will focus on improving business results through the combination of statistical rigor, data analysis, and fast paced execution with an emphasis on driving actionable business recommendations.
• Modeling, Forecasting, and Opportunity Sizing: Both to set goals and help evaluate potential opportunities, this data scientist will be tasked with creating models that ascribe value to content and can inform content development decisions.
• Support Insights and Visualization of Complex Data sets: Development of prototype solutions, mathematical models, algorithms, machine learning models and robust analytics leading to actionable insights communicated clearly and visually.
• Contribute to Product Features: Build/test offers, personalization and recommendation experiences by analyzing complex data sets and developing algorithms to produce results with the goal of increasing customer engagement and retention.
• Partner: Partner closely with business stakeholders to identify and unlock opportunities, and with other data teams to improve platform capabilities around data modeling, data visualization, experimentation and data architecture.
• 5+ years of professional data science/analytical experience
• 5+ years of professional experience using data-building and statistical programming languages: SAS, Python, R, SQL
• Practical experience and expertise in applied statistics and data science methodologies (general advanced data modeling and predictive analytics e.g., multivariate regression analysis, machine learning, forecasting, Bayesian estimation)
• Experience with data exploration utilizing data visualization tools (e.g. Tableau, Looker, Pandas, ggplot2, Plotly)
• Experience with distributed databases and query languages like Spark and Scala
• Ability to think strategically, including interpreting market and consumer information
• Ability to simplify highly complex analyses into terms that are easily accessible and impactful for both written and verbal formats
• Demonstrated ability to present data science results and actionable recommendations to business and technical clients
• Intellectually curious, analytically rigorous, hard-working, good work ethic and an on-point business intuition
• Experience in e-commerce, consumer products, retail or digital products strongly preferred
• Experience in customer analytics, including lifetime value analysis, customer propensity, retention, forecasting, and customer segmentation strongly preferred
• Knowledge and professional application of machine learning algorithms (SVM, Random Forest, Naive Bayes, KNN, etc.) and modern deep learning techniques (PyTorch, Keras/Tensorflow) is a plus
• Bachelor's degree in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research or a related field
• PhD or MS degree in Statistics, Mathematics, Operations Research, CS, Econometrics or related field