Are you passionate about data? Do you like to solve the most complex and high scale (billion + records) data challenges in the world today? Do you have machine learning and qualitative analytics experiences? Do you have background in Big Data, Streaming and/or Data Warehousing tools? Do you want to have an impact in the development and use of new Microsoft data analytics technologies? Would you like a career that gives you opportunities to help Microsoft Azure and 1st party services use cloud computing to do big new things faster, at a high scale? Do you like to gain the deepest insights on service health, customers, usage and custosmer support using Cloud computing technologies? The Azure team is looking for a talented Product Manager to join our efforts to deliver world class Analytics for all services running across Azure. This is an exciting role for a PM who is passionate about data, telemetry and analytics. This position is part of the team that delivers 360 degree views of Azure
This role requires a strong background in data, metrics and data science. This person is responsible to generate actionable insights to improve Azure offerings and Azure fundamentals. Work closely with feature teams to take right data driven decisions to help improve customer experience and data quality. The person will also be responsible for presenting insights and recommendations to leadership teams across various projects and be a strategic Data Science advisor across various teams to inform, influence and support business decisions around feature releases. Geneva Analytics team is building
• Experience in defining and delivering high scale products • Ability to define and build metrics for service fundamentals to help improve the product • Experience with Business Intelligence, and/or Analytics systems • Demonstrated ability to think strategically about business, product, and technical challenges in an enterprise environment • Background in Data mining and qualitative analytics • Understanding of statistical analytical tools and methodologies • Experience with applying data-science and machine learning to business problems • Background in building reports and models for data driven