Data Science Manager
Full Time Job
Data Science Manager (Data Scientist)
The Data Scientist will work within the ESPN Consumer Data Platform – a big data platform responsible for collection of all the consumer integrations across ESPN products and build machine learning models which will impact millions of fans across the world. You will be charged with delivering actionable data insights and data science solutions from ESPN's large and diverse set of first and third party data sources. This data will come from every aspect of the user journey and product experience - user on-boarding, registration, personalization, ad-sales. Data models will be both implicit and explicit. The primary objective will be to apply modern data science techniques to discover patterns in user behavior that can be leveraged to drive three main metrics – user frequency, user engagement and revenue yield. Further, you will be tasked with building models to segment and cluster ESPN's vast amount of digital and broadcast content – marrying these models with user behavior patterning to deliver personalized, unique experiences to each ESPN user.
You will work closely with Product Managers, Designers, Audience Development and Content Development to identify areas of opportunity. You'll work with the entirety of ESPN Technology to build infrastructure and systems that support scalable consumption of the models you build arosss the enterprise. You'll evangelize the work product of the data science function within the company – both upward to executive management and across the organization to peer and constituent groups.
You'll be an excellent communicator, communicating insight, progress and plans to all levels of the company. You will be responsible for creating and approving artifacts designed to document models, requirements, and results..
You'll bring your knowledge of standard data science methods including, but not limited to machine and deep learning, neural net processing, to bear in combination with an understanding of common toolsets such as 'R' or python or similar tools. Furthermore, you will be skilled in standard machine learning models like regression, instance-based, decision tress, Bayesian, clustering and other models and you will use these to build the user, revenue and content systems referenced above.
• Selecting methods for performing advanced data analysis.
• Build machine learning models to solve business problems such as but not limited to recommendations, predictive modelling and churn rate analysis.
• Test and validate models to make sure models are meeting mnimum quality standards.
• Build deep user understanding models, educate business stake holders how to use them to solve business problems.
• Cleary communicate design & development strategies to all stake holders, educate them as and when needed.
• Establishes, supports and maintains standards of the analytics and data science process.
• Work with engineering team to build infrastructure designed to facilitate the construction of models and the exposure of those models to end users throughout the company.
• Work with engineering team to automate daily monitoring of models in production, help troubleshoot issues and make necessary improvements as needed.
• Performing ad hoc analysis, interpreting and communicating results in a clear manner
• Processing, cleansing and verifying the integrity of data used for analysis
• Evangelize the work product of the data science function within the company - both upward to executive management and across to peers and constituent groups.
• Coordinate and execute experiments and create frameworks to support those experiments designed to inform both the strategic and tactical initiatives of the Product team.
• Assist in the preparation of presentations and formal analysis in support of executive decision making and strategy development.
• Minimum 4 years of work experience in data science.
• Expert knowledge of a common data science toolkit such as 'R' or similar.
• Trained in industry standard machine learning methodologies
• Ability to operate effectively in a team-oriented and collaborative environment.
• Excellent communication skills and ability to interact with all levels of end users and technical resources
• Creative thinking and motivated self-starter
• Passionate sports fan and familiarity with ESPN's products and services
• Advanced understanding of machine learning techniques and models.
• Data and analytics/measurement experience in digital or mobile app environment preferred.
• Data driven problem solver with an aptitude for turning large data sets into insights and actions
• Experience working with product and business partners to deliver actionable products beyond theoretical use cases.
• BA/BS in Statistics/Mathematics or related discipline.
• Masters degree in Statistics/Mathematics or related discipline
About The Walt Disney Company:
The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise with the following business segments: media networks, parks and resorts, studio entertainment, consumer products and interactive media. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney's stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished.
This position is with ESPN Internet Ventures, which is part of a business segment we call ESPN.
ESPN Internet Ventures is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Disney fosters a business culture where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a rapidly changing world.