Overview
As Discovery's portfolio continues to grow - around the world and across platforms - the Global Technology & Operations team is building media technology and IT systems that meet the world class standard for which Discovery is known. GT&O builds, implements and maintains the business systems and technology that are critical for delivering Discovery's products, while articulating the long-term technology strategy that will enable Discovery's growing pay-TV, digital terrestrial, free-to-air and online services to reach more audiences on more platforms.
From Amsterdam to Singapore and from satellite and broadcast operations to SAP, we are driving Discovery forward on the leading edge of technology.
In Solutions Delivery, we provide software design and development services to business units around the globe. We provide quality assurance testing services, both manual and automated, for all in-house developed and third party applications supporting our internal customers. In addition, we provide tier two application production support services to over one hundred different applications globally.
Our focus is enterprise application development using state of the art front end development tools and database technology. We follow an agile software development lifecycle methodology for all new development projects and a hybrid waterfall/agile methodology for legacy application modifications. We are currently in the process of migrating many of our applications to Amazon Web Services and transitioning to a continuous integration model.
We support all major revenue generating areas within Discovery including US Ad Sales, International Ad Sales, US Affiliate Sales, and International Affiliate Sales. We also support Discovery's global content supply chain - from idea submission through production through scheduling and airing across the globe.
We are looking for a Data Scientist to play a key role in modeling, software innovation, and automation in a data-driven IT team focused on developing next-generation forecasting and optimization applications. This individual would use applied math (forecasting, machine learning, algorithms, statistical analysis), and cloud/big data skills to advance the development and enhancement of Discovery's operational technologies.
Responsibilities
This is a great opportunity for a highly motivated individual who enjoys not only solving pre-defined problems, but is also comfortable handling unstructured/semi-structured problems. This person will be expected to communicate across multiple functional areas, and must therefore be adept at articulating complex ideas at varying levels appropriate to the audience. The ideal candidate routinely keeps up-to-date with the latest advancements in tech and data science, and is able to apply their findings to building better innovations within their role. This position will be responsible for supporting linear television and digital forecasting needs, and working with software developers, product managers, and other stakeholders to develop algorithmic solutions.
Qualifications

• Master's in a STEM field (e.g. data science, machine learning, computer science, statistics, applied math, operations research, analytics) or equivalent experience/training
• 3-6 years work experience in a quantitative business role
• Experience with statistical and machine learning algorithms and their deployment
• Understanding of forecasting methods and time series analysis
• Knowledge of optimization techniques
• Strong presentation and communication skills; ability to interface with other groups within the organization
• Media experience is a plus (emphasis on the Ad Sales domain)
• Legal right to work in the United States
• "Intrapreneurial" mindset
• Detail obsession

Mathematics

• Statistics: linear/logistic regression, regression analysis, chi square tests, model comparison
• Machine learning: linear models, tree-based models, neural nets, clustering methods, dimensionality reduction
• Optimization: linear/(mixed) integer programming, dynamic programming, metaheuristics
• Time series forecasting: nonlinear regression, decomposable models, ARIMA
• Model performance evaluation

Technology

• Advanced knowledge of SQL, Python for data manipulation, analysis, etc.
• Hands-on experience with Spark, Pyspark
• Modeling libraries (Spark ML, scikit learn, sklearn, PuLP, etc.)
• Statistical computing (R, etc.)
• Business intelligence / data viz tools (Tableau preferred)
• Cloud platform experience (AWS: S3, EMR, EC2, Athena, etc.)
• SQL databases (Oracle, Snowflake, Redshift)