Staff Data Scientist, Product Growth, CNN+

Company: Warner Media Group
Location: Atlanta, Georgia, United States
Type: Full-time
Posted: 13.AUG.2021


The JobWe are seeking a Staff Data Scientist to serve as the primary technical lead of Product Growth Data Science within our Data Products ...


The JobWe are seeking a Staff Data Scientist to serve as the primary technical lead of Product Growth Data Science within our Data Products and Insights team, serving as a subject matter expert in the methods and technologies for acquiring, activating, engaging, and retaining CNN subscribers. This individual will be a thought leader in building predictive analytics and product experimentation capabilities that will optimize the growth of CNN+, our direct-to-consumer product. This person will also be responsible for mentoring and growing a team of engineering- and statistically- minded data scientists and enhancing the wider Analytics and Science culture at CNN. Core areas of focus and outcomes include: Customer and Product-oriented - You collaborate with product stakeholders to uncover the needs for data products that support forecasting insights, on-platform acquisition, churn mitigation, and experimental design and analysis of emerging products/features. Applied math and stats - You know how to lead a team to decide whether a business problem requires advanced statistics, statistical learning, or machine learning, and how to effectively transform each into a scalable data product. You possess the skills to develop and socialize best practices in ML-application, stochastic and probabilistic statistics, and experimental design and evaluation among your team, and their relevance to non-technical stakeholders. Engineering solutions - Prototype and scale engineering solutions for building data science capabilities, supporting work through the entire Data Science Lifecycle. This role will be expected to support a growing analytics organization, with ample room for methodological and technological innovation. This is a collaborative role. You'll work to accomplish objectives with cross-functional teams and peers, including product managers; revenue, content, and design strategists; engineers; and consumer science /audience researchers. You'll lead through influence on challenge assumptions in favor of building and maturing a data-driven, insightful culture that has the insights it needs to make informed decisions fast and deliver impactful experiences. The DailyServe as central point-of-contact for predictive and prescriptive growth analytics for CNN+, building and socializing the use of data science capabilities to ensure product/business growth within research, analytics, product, and engineering teams. Lead and contribute to detailed data science projects such as identifying content clusters and audience segments, revenue trends and user lifetime value, and other predictions that create tangible insights that inform content strategy, planning, and investment. Scale and deploy models that provide access to data, dashboards, and critical insights - and conduct training to empower teams to self-serve the data and dashboards they need. Build proactive relationships with peers and cross-functional teams in the company so you understand the relevant questions and needs of the business and use that to advise your analysis. Partner with data platform and engineering team to continually interrogate the tools, methods, and processes supporting analysis to optimize the cost and function of our tech stack. The Essentials8+ years' experience working on or with cross-functional data science and analytics teams, utilizing various mathematical methodologies (probability theory, causal analysis, graph theory), data manipulation and programming languages (SQL, Python, Scala), and ML engineering tools (Airflow, Metaflow, DBT). Experience with AWS services and resources is preferred. Ability to build the components necessary for managing the machine learning lifecycle as it pertains to business-focused data science. Demonstrated ability to manipulate, analyze, and interpret large amounts of data, organize findings, and translate into actionable insights. A quick learner can work independently in a matrixed environment, adaptability and a strong self-teaching ethic. Thrives in a fast-paced, dynamic, and agile environment that can pivot quickly to capture opportunities from the users and business's changing needs. Outstanding organizational, interpersonal (ability to influence without hierarchy) and communication skills. Academic background in quantitative field such as econometrics, behavioral statistics, finance, or computer science a plus.

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