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Senior Manager Data
2 months ago
developing talent and mature D&A culture;
building trust and managing data;
and evolving technologycapabilities.This role will report to the Global CTO and work closely with the executive leadership team and business/functional management team, globally.Ideal candidate should have:-Experience in building advanced analytics models across one or more areas of Predictive/Prescriptive Analytics, and Image Processing.Strong Data Management, data governance, data ownership, data architecture skills.Should be able to work independently in collaborations with functional and global teams. Work in cross-disciplinary project teams of database specialists, IT specialists, business subject-matter experts and agronomists who will bring the domain expertise to our data-driven solutions.Candidates need to demonstrate that they were instrumental in executing end-to-end significant data analytics projects.Experience with analytical packages, SQL, Python, R, Spark, Statistical packages like Statistics, Minitab, Azure cloud, notebooks (data bricks/Jupyter) is preferred.ESSENTIAL FUNCTIONS:Maintain accountability for exploiting the value of enterprise information assets, and of the analytics used to render insights for decision making, automated decisions and augmentation of human performance. Be the corporate leader of data-driven insights and use cases that help support and unlock strategic and tactical business opportunities.Build partnerships with leadership teams across the organization and establish a shared vision for managing data as a business asset — to exploit data and analytics capabilities to maximize the value derived from data assets.Expanding our capabilities beyond description analytics to predictive/prescriptive analytics leverage data science, machine learning & AI.Foster the creation of a data-driven culture, related competencies, and data literacy across the enterprise. Lead these transformation efforts by developing D&A talent and maturing the capability of the organization, especially in the space of AI.Establish and maintain trust in data assets by instituting governance mechanisms for data and algorithms used for analysis, analytical applications, and automated decision-making.
