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About this job

DISH is a Fortune 200 company with more than $15 billion in annual revenue that continues to redefine the communications industry. Our legacy is innovation and a willingness to challenge the status quo, including reinventing ourselves. We disrupted the pay-TV industry in the mid-90s with the launch of the DISH satellite TV service, taking on some of the largest U.S. corporations in the process, and grew to be the fourth-largest pay-TV provider. We are doing it again with the first live, internet-delivered TV service – Sling TV – that bucks traditional pay-TV norms and gives consumers a truly new way to access and watch television.

 

Now we have our sights set on upending the wireless industry and unseating the entrenched incumbent carriers.

 

We are driven by curiosity, pride, adventure, and a desire to win – it’s in our DNA. We’re looking for people with boundless energy, intelligence, and an overwhelming need to achieve to join our team as we embark on the next chapter of our story.

 

Opportunity is here. We are DISH.

Skills - Experience and Requirements
A successful data scientist will have the following:
• 3-5 years of relevant professional experience in data science and business analytics; or equivalent combination of education and experience with a degree in computer science, mathematics, statistics, economics, finance, or business.
• Working experience with data modeling, programming and statistical analysis tools (e.g. Python, R), data querying and database management (e.g. Hadoop, Teradata) and data visualization (e.g. Tableau)
• Strong quantitative and analytical skills with ability to create meaningful presentations that tell a story focused on insights, not just data
• A self-starter and creative problem solver who can navigate through unknown situations with minimal guidance and drive projects toward completion
• Excellent interpersonal skills and ability to be flexible in a fast-pacing sales environment

Job Duties and Responsibilities
DISH Media Sales, the advertising sales division of DISH Network, provides smart, cost-effective media solutions that complement those of traditional national cable. Headquartered in New York, DISH Media Sales is part of the DISH Network family committed to offering the highest-quality entertainment and most advanced technology all at an unbeatable value.

We are looking for an exceptional data scientist to join our Pricing and Inventory team which is responsible for the Media Sales strategy, research, pricing and inventory management. The team work cross-functionally with Sales, Finance, Analytics, Operation and Data warehouse. He/She will report to the Senior Manager of Pricing and Inventory, and work with the largest continuous set-top-box data set in the industry to help drive revenue growth through pricing and inventory optimization strategy. The primary focus will be in applying data mining techniques and statistical analysis on advertising viewership and revenue KPI forecasting. You should be passionate about building reporting automation and prediction systems, finding insights in large datasets, synthesizing and communicating results, and driving practical business impact.

Job duties and responsibilities include but are not limited to:
• Forecast advertising inventory demand in term of traditional linear spots and advanced audience-targeted addressable spots to optimize inventory allocation by using ad traffic, viewership, financial and industry data
• Model trends across advertising inventory supply, utilization, sellout rates to forecast future usage of corresponding inventory buckets
• Track and analyze addressable segment requests and make recommendations on future ad campaign targeting strategy
• Work with the sales group and pricing team on new advertising package generation, rate card creation and pricing decisions based on inventory and yield analysis
• Synthesize methodology and data into actionable business strategy on yield management and communicate findings to upper management, sales and media planning teams
• Suggest and implement improved data management, data mining and technology enhancements to support scaling the business; work with IT and data warehouse as necessary
• Communicate with internal and external data partners to define and develop business revenue KPIs as well as new viewer measurement data and metrics