Our Team

The Global Data & Advanced Analytics (GDA) team enables Discovery to turn data into action. Using big data platforms, statistical inference, machine learning, data visualization, and self-service analytics, this team supports company-wide efforts to drive audiences & enhance consumer engagement. Join an innovative, high impact team helping to serve passionate fans around the globe with content that inspires, informs, and entertains.

The Role
The Senior Data Scientist will be responsible for managing and executing high impact data science projects to support our Direct-to-Consumer business partners. These efforts will include but are not limited to

1) the projection of customer lifetime value across multiple media platforms.

2) hypothesis testing relative to customer engagement, segmentation, and churn.

3) time series analyses of customer lifecycles and product features/development. Specifically, you will be responsible for the development and execution mathematical/statistical analyses as well as the implementation of operationalized algorithms and models.

The ideal technical skill set would include applied experience implementing methodologies such as survival analysis, RFM modelling via Pareto/NBD and other parametric distributions, time series analysis, and non-parametric modelling approaches to time-based predictions such as neural networks (CNN, LSTM, etc.).

You’ll need to be an innovative forward-thinker who will conduct end-to-end data science initiatives, work collaboratively with other data scientists as well as key business partners, and contribute directly to existing and emerging business strategies and goals. Communication and ability to thrive in a team environment are essential, as are strong technical skills, creativity and attention to detail, and experience conducting data science projects from use case definition to final product delivery.

Responsibilities

• Technical Responsibilities

1. Apply data mining techniques to cleanse and explore large, complex data sets in preparation for further analysis
2. Apply appropriate data reduction, feature selection, and feature engineering techniques
3. Develop, validate, and operationalize sound mathematical and statistical algorithms and models, with an eye toward deploying on large scale systems
4. Develop and implement hypothesis tests
5. Review, make enhancements to, and execute operationalized algorithms and models
6. Develop data products to communicate insights to business partners
7. Collaborate with data & technology teams to create repeatable processes and scalable data products

• Project Scoping and Execution

1. Meet with business partners to flush out use cases and key requirements
2. Collaborate with data and technology teams to identify and source data sets required for analyses
3. Provide regular updates to and receive strategic direction from global data science team lead
4. Agree on project deliverable timelines with data science team & relevant data, technology, and business partners; manage project execution according to agreed timelines
5. Provide direction to senior/junior data scientists and review data science approaches, code, & deliverables
6. Prepare and communicate analytic insights to senior level management and business partners in clear business terms
7. Identify appropriate data science solutions as new data-centric business queries arise
8. Stay current with new data science methods, technologies, and industry trends

Preferred Qualifications

(**Required Qualifications)

• Master’s or PhD degree in a quantitative field (statistics, finance, econometrics, etc.)
• Minimum of 5+ years proven business experience and technical expertise in data science
• **Applied experience related to customer lifetime value projection, including methodologies such as survival analysis; RFM/BTYD frameworks; Pareto/NBD models and other parametric approaches/distributions; and non-parametric approaches such as neural networks (CNN, LSTM, etc.)
• **Experience with time-series analysis, time-based validation, hypothesis testing, clustering, regression, & classification
• **Experience cleansing and preparing large, complex datasets for analysis
• **Expertise in statistical programming languages such as R or Python (StatsModel, NumPy, SciPy, scikit-learn, etc.)
• **Experience with SQL in cloud-based data stores required; Amazon Web Services (RedShift, S3, EC2, EMR, etc.) and Apache Spark preferred
• Professional-level expertise in developing, validating, and executing algorithms and models on large scale systems
• Familiarity with data visualization applications, like Tableau or RShiny
• Self-starter with strong analytical, critical thinking, and problem-solving skills
• Excellent communication skills -- ability to present complex information in a concise and compelling manner
• Prior media or direct-to-consumer industry experience preferred
* Must have the legal right to work

Discovery Communications, Inc. is an equal opportunity employer. Discovery is committed to being an employer of choice, not just a good place to work, but a great and inclusive place to work. To that end, we strive to recruit and maintain a workforce that meaningfully represents the diverse and culturally rich communities that we serve. Qualified applicants will receive consideration for employment without regard to their race, color, religion, national origin, sex, sexual orientation, gender identity, protected veteran status or disabled status or, genetic information.

We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including but not limited to all local Fair Chance Ordinances.

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