Data Scientist, Theatrical Marketing represents an exciting new role positioned at the fast-moving intersection of film marketing strategy, digital ad tech, and big data / predictive modeling. The role is built for a self-starter, and creative, quantitative thinker; someone comfortable pushing for structured insights amidst disparate data sets, and excited about applying data and analytics to evolving Theatrical Film Marketing.
The role reports to the VP of Analytics Insights and will join a practice charged with developing a roadmap for the Studio’s integration of data into their decision-making lifecycle. Success will require balancing processing and translating business needs, with the ability to be hands-on in the data, building machine learning models (R, Python, etc.) and other granular statistical analyses.
The Data Scientist, Theatrical Marketing must have a proven track record of extracting meaningful business insights from data. From data wrangling to developing analytical frameworks and applying advanced statistical techniques, this person must have the experience to proactively translate business questions into a comprehensive, team-based project plan. Working across consumer, marketing and media-related data sets, the Director, Marketing Data Science will be required to balance a long-term roadmap with ad-hoc projects impacting the next film release. Success will require a self-starter attitude, curiosity and initiative-someone who wants to change the fundamental approach to movie marketing.
Machine Learning Initiatives: Predictive Box Office Modeling, Audience Content Insights
• Long Lead Signal Enhancement: support the improvement of predictive box office tools, calibrating a wide variety of data sets to support robust predictive outputs. Creative thinking will be critical to generating meaningful insights from many disparate digital signals datasets.
• Audience / Content Insights Ad-hoc Studies: using available data sets and machine learning tools to enable both modular and comprehensive research into drivers of moviegoing behavior, content effectiveness and an understanding of related proxy measures and data sets. Scope of data and analysis dependent on business questions and iterative feedback to uncover new, more meaningful questions.
1st Party Audience Data Strategy (Digital Media)
• Audience Segmentation Modeling: assist in first phase of assessment of first-party consumer data to determine value to improving effectiveness of media targeting. Longer-term roadmap includes researching new ways of modeling and predicting end-user behavior, including designing experiments to do so.
• User-Level Audience Insights: build a long-term vision around acquisition and exploration of granular user-level data to shed more light on the complex moviegoing ”customer journey”. Determine the role of proprietary CRM, log-level data in deepening our understanding of who is likely to see a movie and the messaging most likely to convert them.
BA/BS degree required with technical focus (e.g. mathematics, computer science, physics
• MS or PhD degree preferred
• Minimum of 4-5 years of progressively complex related experience
• Business experience in media industry preferred, but not required
The ideal candidate will be skilled/qualified in:
• Advanced Statistics Supervised and unsupervised machine learning models, including regularization, feature engineering, training, as well as interpretation and integrity. Experience with clustering, affinity analysis, segmentation, customer profiling.
• Specific familiarity with xgboost, caret, ggplot2 packages
• Programming Expertise with SQL data models (logical, physical, conceptual), R (required), Python (a plus, NumPy, pandas, scikit-learn), R Studio Shiny apps (also a plus), including familiarity with databases, data wrangling, maintenance, cleaning. Comfort with ETL, API strategies.
• Visualization Presentation Represent complex information in easily understood visualization (including Tableau, PowerPoint, etc.). Communicating clearly to executives, technology partners, agencies, and contributing to projects and meetings
• Project Management Strong attention to detail, willingness to wear multiple hats, building and tracking a work plan in a fast-based environment
• Marketing Measurement Methodologies Familiarity around measuring digital impact (MMM, closed loop studies, geographic and pacing variability modeling, regression)
The ideal candidate will have the ability/qualifications to:
• Analyze and organize large data sets to create a cohesive story that can inform marketing strategies
• Understand in depth, design and inform statistically valid tests with test and control groups and to manage the process of identifying testing strategies.
• Experiment with various tools and technologies, with the end goal of creating innovative data-driven insights at a quick pace.
• Handle data wrangling, cleansing, QC, as new data is considered. Success will require assisting IT team to acquire/transfer, store, organize and operationalize data.
• Provide strategic vision to a growing data science team, including developing data structures and analytical frameworks that will sustain our long-term vision.
• Work collaboratively and horizontally across multiple teams with fragmented, vertical (title-by-title) priorities.
• Translate business objectives into analytical functions, including ability to quantitatively assess risk.
The ideal candidate will have knowledge of/be qualified in:
• Business Processes: Experience with Agile methodology (Jira), Git
• Digital media/marketing landscape Familiarity with addressable media strategies, CRM, ad-tech (i.e. Krux, DCM), audience buying platforms and methodologies, digital KPIs
• Film marketing data science: basic strategies, campaign tactics and common social/digital KPIs. Passion for movies, and knowledge of existing industry tools, studies, methodologies and data sets is a major plus!