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The Head of Content & Creative will develop and execute ZS's creative strategy and lead the content and design teams. This role involves establishing KPIs, fostering innovation, leveraging AI, and enhancing promotional assets to elevate the brand's reputation in the market.
As a Product Data Scientist (Senior Customer Success Lead) at ZS, you will lead client engagements by delivering impactful analytics solutions, translating client requirements into data science models, and providing insights to solve complex business problems. You will collaborate with project teams and utilize advanced analytics frameworks and data engineering skills to optimize client operations.
The Product Data Scientist (Sr. Lead, Customer Success) is responsible for leading client engagement, delivering insights, and overseeing data science modeling. This role involves developing advanced analytics processes and operational pipelines, translating client needs, and presenting data-driven solutions for business optimizations.
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The Product Data Scientist will lead client engagements to deliver impactful data science solutions, translating requirements into actionable insights. Responsibilities include developing advanced analytics processes and operational pipelines while leveraging problem-solving frameworks and analysis tools to address client business challenges.
The Product Data Scientist will lead client-facing projects, delivering impactful analytics solutions and translating client needs into data science modeling. They will build operational pipelines and present data-driven insights to help clients optimize their business problems through advanced analytics and AI frameworks.
As an Applied AI Scientist at ZS, you'll develop advanced algorithms and statistical techniques to analyze large datasets. You will evaluate technologies for the analytical platform, own the development of capabilities, and contribute to thought leadership through research and publication.
The Applied AI Scientist will develop advanced algorithms for solving high-dimensional problems, execute statistical and data mining techniques on large data sets, evaluate emerging datasets for analytics, and contribute to thought leadership. They will also focus on feature engineering from varied data sources and expertise in machine learning algorithms.
The Applied AI Scientist will develop advanced algorithms and execute statistical techniques on large datasets to identify trends. Responsibilities include evaluating emerging datasets, owning the development of assets for scaling capabilities, and contributing to the firm's thought leadership through research and publication.
As a Machine Learning Engineer at ZS, you will build and monitor model pipelines, scale algorithms for large datasets, enhance ML engineering platforms, implement ML Ops, and ensure high-quality deliverables. You will also conduct research on architecture patterns and collaborate with global teams to deliver projects efficiently.
This role involves developing and implementing advanced algorithms to solve complex problems, executing data mining techniques on large datasets, evaluating new datasets and technologies, and contributing to the firm's thought leadership through research and publications.
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