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Senior Data Scientist/Statistician

Discovery hires the very best and brightest talent who are enthusiastic and passionate to fulfill the company's mission of empowering people to explore their world and satisfy their curiosity.

In exchange for their talent and drive, employees are provided with an engaging, diverse workplace and the resources they need to learn, thrive and grow in their careers.

Position Summary

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/Statistician will sit within the centralized GDA team and will be responsible for managing and executing data science projects. The role will support business partners across the company, with a particular focus in the direct-to-consumer product space. Example projects could include: time series-based analyses of customer engagement and/or content ratings; predictive modelling of customer conversion and churn; product valuation, including hypothesis testing and forecasting; and customer clustering and segmentation across products and platforms. 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 with inferential statistical approaches such as time series analysis, regression, classification, generalized linear modelling, multi-level modelling, clustering, survival analysis, and experimental design. The ideal candidate also brings experience working with large datasets and operationalizing/deploying models in cloud environments.

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.

Key Areas of Responsibility

• 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 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. Prepare and communicate analytic insights to business partners
  6. Stay current with new methods, technologies, and industry trends

Preferred Qualifications

(**Required Qualifications)

• Master's or PhD degree in a quantitative field (statistics, econometrics, etc.)
• Minimum of 5+ years proven business experience and technical expertise in data science
• **Applied experience with inferential statistical approaches such as time series analysis, regression, classification, generalized linear modelling, multi-level modelling, clustering, survival analysis, and experimental design, and hypothesis testing
• **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

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

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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If you are an individual with a disability and need an accommodation during the application process, please send an email request to [email protected]

Nearest Major Market: Washington DC

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