The Sr. Data Scientist is responsible for helping to develop the actionable insights behind CNN's emerging personalization, recommendation, and search strategy. This role will transform first- and third- party data into reliable quantitative insights about the internal and external performance of recommendation and search features.
• Leverage our internal data platforms to quantify and identify patterns in recommendation freshness and relevance, content diversity, training candidate optimization, and user informed-ness. Should have expertise in inferential and causal statistics, preference will be given to candidates with some experience in NLP and text analytics using python or R.
• Develop, maintain, and continuously improve the automation behind diagnosing the performance of recommendation engines and search, with an eye toward empowering analysts to feed to feed those calculations to dashboards.
• The ability to break down quantitative historic and experiment findings into meaningful insights and develop recommendations that lead to informed decision-making.
• Partner closely with and serve as a statistics and evaluation expert for personalization and search engineers.
• Participate in answering ad hoc project and data requests from various business units and organizations about the impact and performance of personalization and search.
• Design and build reports and/or dashboards that clearly communicate quantitative analyses of consumption patterns and content relationships.
• Build clear documentation around ad hoc analyses, methodology, and data definitions for raw and munged data.
• Collaborate with both the data organization and its technology partners to identify opportunities for new data products.
• 5+ years' experience working on or with cross-functional analytics teams
• 3+ years data science experience querying databases (SQL), leveraging a scripting language (R/Python) to analyze data at scale, and deploying/automating/monitoring calculations
• Domain knowledge of personalization and/or search products, including demonstrated ability to form questions and design measurement heuristics
• 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 business, marketing, behavioral science, or applied math a plus
Jobcode: Reference SBJ-g3k4pq-3-235-120-150-42 in your application.