Position Summary

Our Team

The Global Data & Advanced Analytics (GDA) team enables Discovery to turn data into action. Using big data platforms, data warehousing and business intelligence technology, audience data, advanced analytics, data science, visualization, and self-service analytics, this team supports global company efforts to increase revenue, drive audiences, and enhance consumer engagement. Join a team that supports high impact business partners with driving innovation through data science.

The Role

The Director of Data Science is a critical role that will support GDA’s business partner, Media Strategy and Analytics (MSA). MSA acts as an internal data-driven media agency that handles the strategy, execution, optimization and reporting of all paid & owned media vehicles with the goal of driving viewership across TV, digital and direct-to-consumer products for all of Discovery, Inc’s 16+ networks (Discovery, TLC, HGTV, Food Network, MotorTrend, GOLFTV, etc.).

The position will work with a wide array of small and big data sets, applying statistical analysis, machine learning and AI tools and predictive algorithms to quantify the relationship between outcomes and media spend, audience segmentation and targeting, timing, placement decisions and other aspects of our media strategy.

In addition to applying your technical prowess and analytical mind, you will be expected to collaborate with stakeholders across GDA & MSA to gain an expert understanding of the business and to identify ways to apply data science to improve it.

Responsibilities

1. Use cutting edge data science tools and techniques to explore first-party and third-party datasets to identify, validate and quantify relationships between variables.
2. Create and investigate hypotheses related to audience engagement, ratings, content performance and monetization.
3. Lead analysis of underlying drivers and relevant patterns across multiple campaigns to uncover audience segmentation opportunities, inform media planning strategies and optimize performance models
4. Develop and evolve methodologies for measuring business results and using the available data to guide campaign planning and optimization activities.
5. Review and weigh in on the methodologies used by our outside partners and vendors.
6. Identify innovative uses of data and/or data technology that can give MSA a competitive marketplace advantage
7. Be an active evangelist for strong scientific method in the company.
8. Apply statistical techniques to the analysis of complex datasets.
9. Use statistics to isolate the impact of individual factors from the noise of complicated business processes containing many unknowns.
10. Lead the application of AI and machine-learning tools to the media planning and buying process and develop new proprietary tools, prioritizing IP ownership.
11. Use predictive analytics techniques to create and maintain projections for the results of marketing campaign plans.
12. Work with the team to “close the loop” between the analysis/planning and the results data, enabling agile optimization of campaigns.

Requirements

* PhD or Masters in Statistics, Mathematics, Economics or similar degree (PhD preferred but not required)
* 8+ years of experience in end-to-end statistical analysis, data science, and machine learning lifecycles at an enterprise level
* Experience in the TV/Digital media space a plus
* Strong understanding of methods in statistical analysis (e.g., data distributions, regression analysis, experimental design, hypothesis testing, etc.)
* Expertise in exploratory data analysis, data cleaning, data wrangling, feature reduction, and feature engineering
* Strong problem-solving skills, able to break down a large problem into smaller, solvable components
* Extensive experience with different Data Science methods such as clustering, classification, regression, time series, & optimization
* Advanced programming skills in modern languages including Python, R, C#, Java, Scala and Go (Python required)
* Experience with a range of machine learning related frameworks and libraries, such as Python scikit-learn, Pandas, StatsModels, Pandas, Keras, TensorFlow
* Ability to seek empirical evidence through proofs of concept, statistical validation and external research
* Ability to effectively collaborate with other data scientists, analysts, data engineers and business stakeholders
* Experience with BI and data visualization tools like R Shiny & Tableau
* Experience with AWS (RedShift, S3, EC2, EMR, etc.) and parallel processing or distributed computing a plus (e.g., Apache Spark)
* Excellent written and verbal communication skills; with the ability to communicate the results of your work in meaningful ways

* Must have the legal right to work in the United States