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$ cat jobs/lts-insights-manager-product-insights-linkedin3-4b01a15ad99d.json

LTS Insights Manager, Product Insights

Linkedin3·Worldwide·Chicago, US·mid
data science
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LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works. This role will be based in Atlanta, Bellevue, Chicago, Carpinteria, Detroit, New York City, Omaha, Sunnyvale, San Francisco, or Washington, D.C. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. We are seeking a highly motivated and experienced Insights Manager to join our team. The ideal candidate will be responsible for leading a team of Insights Program Managers and Data Engineers to transform our operations and data strategy for Scaled Insights. This role will lead a high-performing data team that bridges strategic data initiatives with hands-on technical execution. This role ensures alignment between business goals and data capabilities, fostering a culture of innovation, accountability, and continuous learning. Responsibilities : Strategic Leadership Translate business objectives into a clear data strategy and roadmap. Prioritize initiatives that drive measurable business impact. Collaborate cross-functionally with Data Science, Engineering, Insights SMEs and business stakeholders. Technical Oversight Guide the team in building scalable data pipelines, AI infrastructure, and monitoring platforms. Ensure best practices in data governance, quality

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